# fal ## Docs - [fal api](https://fal.ai/docs/api-reference/cli/api.md) - [fal apps delete](https://fal.ai/docs/api-reference/cli/apps/delete.md) - [fal apps delete-rev](https://fal.ai/docs/api-reference/cli/apps/delete-rev.md) - [fal apps list](https://fal.ai/docs/api-reference/cli/apps/list.md) - [fal apps list-rev](https://fal.ai/docs/api-reference/cli/apps/list-rev.md) - [fal apps rollout](https://fal.ai/docs/api-reference/cli/apps/rollout.md) - [fal apps runners](https://fal.ai/docs/api-reference/cli/apps/runners.md) - [fal apps scale](https://fal.ai/docs/api-reference/cli/apps/scale.md) - [fal apps set-rev](https://fal.ai/docs/api-reference/cli/apps/set-rev.md) - [fal auth](https://fal.ai/docs/api-reference/cli/auth.md) - [fal create](https://fal.ai/docs/api-reference/cli/create.md) - [fal deploy](https://fal.ai/docs/api-reference/cli/deploy.md) - [fal doctor](https://fal.ai/docs/api-reference/cli/doctor.md) - [fal environments](https://fal.ai/docs/api-reference/cli/environments.md) - [fal files](https://fal.ai/docs/api-reference/cli/files.md) - [CLI Reference](https://fal.ai/docs/api-reference/cli/index.md): Complete reference for the fal command-line interface - [Installation](https://fal.ai/docs/api-reference/cli/installation.md) - [fal keys](https://fal.ai/docs/api-reference/cli/keys.md) - [fal profile](https://fal.ai/docs/api-reference/cli/profile.md) - [fal queue](https://fal.ai/docs/api-reference/cli/queue.md): Manage application queues. - [fal run](https://fal.ai/docs/api-reference/cli/run.md) - [fal runners](https://fal.ai/docs/api-reference/cli/runners.md) - [fal secrets](https://fal.ai/docs/api-reference/cli/secrets.md) - [fal teams](https://fal.ai/docs/api-reference/cli/teams.md) - [Dart Client](https://fal.ai/docs/api-reference/client-libraries/dart/index.md): fal client library for Flutter applications - [Client Libraries](https://fal.ai/docs/api-reference/client-libraries/index.md): Libraries for calling fal AI models from your applications - [auth](https://fal.ai/docs/api-reference/client-libraries/javascript/auth.md): API reference for @fal-ai/client auth - [client](https://fal.ai/docs/api-reference/client-libraries/javascript/client.md): API reference for @fal-ai/client client - [JavaScript Client](https://fal.ai/docs/api-reference/client-libraries/javascript/index.md): API reference for @fal-ai/client - [middleware](https://fal.ai/docs/api-reference/client-libraries/javascript/middleware.md): API reference for @fal-ai/client middleware - [queue](https://fal.ai/docs/api-reference/client-libraries/javascript/queue.md): API reference for @fal-ai/client queue - [realtime](https://fal.ai/docs/api-reference/client-libraries/javascript/realtime.md): API reference for @fal-ai/client realtime - [response](https://fal.ai/docs/api-reference/client-libraries/javascript/response.md): API reference for @fal-ai/client response - [retry](https://fal.ai/docs/api-reference/client-libraries/javascript/retry.md): API reference for @fal-ai/client retry - [storage](https://fal.ai/docs/api-reference/client-libraries/javascript/storage.md): API reference for @fal-ai/client storage - [streaming](https://fal.ai/docs/api-reference/client-libraries/javascript/streaming.md): API reference for @fal-ai/client streaming - [types.client](https://fal.ai/docs/api-reference/client-libraries/javascript/types.client.md): API reference for @fal-ai/client types.client - [types.common](https://fal.ai/docs/api-reference/client-libraries/javascript/types.common.md): API reference for @fal-ai/client types.common - [utils](https://fal.ai/docs/api-reference/client-libraries/javascript/utils.md): API reference for @fal-ai/client utils - [Kotlin / Java Client](https://fal.ai/docs/api-reference/client-libraries/kotlin/index.md): fal client library for Android and JVM applications - [fal_client](https://fal.ai/docs/api-reference/client-libraries/python/fal_client.md): API reference for fal_client - [Python Client](https://fal.ai/docs/api-reference/client-libraries/python/index.md): API reference for fal-client Python package - [Swift Client](https://fal.ai/docs/api-reference/client-libraries/swift/index.md): fal client library for iOS, macOS, tvOS, and watchOS - [Reference](https://fal.ai/docs/api-reference/index.md): Complete API and SDK reference documentation for fal - [Authentication](https://fal.ai/docs/api-reference/platform-apis/authentication.md): Platform APIs require API keys for secure access to your user or team's data. - [Platform APIs for Accounts](https://fal.ai/docs/api-reference/platform-apis/for-accounts.md): Programmatic access to account billing information, FOCUS-compliant cost reports, and model access controls - [Platform APIs for Compute](https://fal.ai/docs/api-reference/platform-apis/for-compute.md): Programmatic access to compute instance management, lifecycle control, and monitoring - [Platform APIs for Keys](https://fal.ai/docs/api-reference/platform-apis/for-keys.md): Programmatic access to API key management, creation, and deletion - [Platform APIs for Models](https://fal.ai/docs/api-reference/platform-apis/for-models.md): Programmatic access to model metadata, pricing, usage tracking, and analytics - [Platform APIs for Serverless](https://fal.ai/docs/api-reference/platform-apis/for-serverless.md): Programmatic access to serverless apps metadata and analytics - [Platform APIs for Workflows](https://fal.ai/docs/api-reference/platform-apis/for-workflows.md): Programmatic access to workflow metadata, listing, and details - [Introduction to Platform APIs](https://fal.ai/docs/api-reference/platform-apis/index.md): Platform APIs provide programmatic access to platform resources including model metadata, pricing information, usage tracking, and analytics. - [Platform Metadata](https://fal.ai/docs/api-reference/platform-apis/meta.md): Returns platform metadata including webhook IP ranges for allowlisting. - [OpenAPI Schema](https://fal.ai/docs/api-reference/platform-apis/openapi-schema.md): The fal Platform API is documented using the OpenAPI 3.1 specification format. - [fal.api](https://fal.ai/docs/api-reference/python-sdk/api-reference.md): API reference for fal.api - [SyncServerlessClient](https://fal.ai/docs/api-reference/python-sdk/client.md): Synchronous Python client for fal Serverless. Manage apps, runners, and deployments programmatically. - [fal](https://fal.ai/docs/api-reference/python-sdk/fal.md): API reference for fal - [Python SDK](https://fal.ai/docs/api-reference/python-sdk/fal-app-reference.md): API reference for the fal Python package - [fal.distributed](https://fal.ai/docs/api-reference/python-sdk/fal-distributed.md): API reference for fal.distributed - [fal.exceptions](https://fal.ai/docs/api-reference/python-sdk/fal-exceptions.md): API reference for fal.exceptions - [fal.toolkit](https://fal.ai/docs/api-reference/python-sdk/fal-toolkit.md): API reference for fal.toolkit - [fal.toolkit.image.nsfw_filter](https://fal.ai/docs/api-reference/python-sdk/fal-toolkit-image-nsfw-filter.md): API reference for fal.toolkit.image.nsfw_filter - [Product Changelog](https://fal.ai/docs/changelog.md): Latest features and updates to the fal platform - [Introduction to Compute](https://fal.ai/docs/documentation/compute/index.md): Dedicated GPU instances for training, fine-tuning, and workloads that need sustained access to hardware. - [Pricing](https://fal.ai/docs/documentation/compute/pricing.md): How billing works for fal Compute. - [Quickstart with Compute](https://fal.ai/docs/documentation/compute/quickstart.md): Get up and running with fal Compute in minutes. This guide will walk you through provisioning your first GPU instance and connecting to it. - [Caching](https://fal.ai/docs/documentation/deployment/caching.md): How fal's multi-layer caching system reduces cold start times by caching Docker images, model weights, and compiled artifacts. - [Deploy to Production](https://fal.ai/docs/documentation/deployment/deploy-to-production.md): Deploy your fal App to production with persistent URLs, authentication, and automatic scaling. - [Machine Types](https://fal.ai/docs/documentation/deployment/machine-types.md): Available machine types, specifications, and guidance on choosing the right GPU for your workload. - [Manage Deployments](https://fal.ai/docs/documentation/deployment/manage-deployments.md): Once your models are deployed to production, you need tools and strategies to manage them effectively. This guide covers listing deployments, monitoring application health, managing multiple versions, and safely removing models. - [Manage Environments](https://fal.ai/docs/documentation/deployment/manage-environments.md): Organize your fal Serverless applications, secrets, and configurations across different stages of your development workflow using environments. Create isolated spaces for development, staging, and production deployments. - [Deployment Overview](https://fal.ai/docs/documentation/deployment/overview.md): Ship your fal applications to production, manage revisions and environments, configure scaling, and choose the right machine type. - [Understanding Requests](https://fal.ai/docs/documentation/deployment/requests.md): How requests flow through fal's infrastructure, from submission through queue, dispatch, processing, and retries. - [Rollbacks & Revisions](https://fal.ai/docs/documentation/deployment/rollbacks.md): Manage app revisions, roll back to previous versions, and restart runners. - [Understanding Runners](https://fal.ai/docs/documentation/deployment/runners.md): What runners are, how they start, process requests, scale, and shut down. - [Scaling Parameter Reference](https://fal.ai/docs/documentation/deployment/scale-your-application.md): All scaling parameters for controlling runners, cold starts, and costs. - [Updating Your Configuration](https://fal.ai/docs/documentation/deployment/scaling-configuration.md): How to set scaling parameters via code, CLI, or dashboard -- and how they behave across deploys. - [Add Health Check Endpoint](https://fal.ai/docs/documentation/development/add-health-check-endpoint.md): Add a health check endpoint to your fal app so the platform can detect and replace unhealthy runners. - [Optimize Routing Behavior](https://fal.ai/docs/documentation/development/advanced/optimize-routing-behavior.md): Use routing hints to direct requests to runners that already have the right model or state loaded in memory. - [App Lifecycle](https://fal.ai/docs/documentation/development/app-lifecycle.md): The complete lifecycle of a fal app, from writing code to runner shutdown. - [Application Setup](https://fal.ai/docs/documentation/development/app-setup.md): Prepare your app's runtime environment: load models, download weights, and configure persistent storage. - [Calling Your Endpoints](https://fal.ai/docs/documentation/development/calling-your-endpoints.md): How to call your deployed serverless endpoints using the fal client SDKs. - [Environment and Runtime](https://fal.ai/docs/documentation/development/container-setup.md): Choose how to define the environment your fal app runs in. - [Docker Templates and Best Practices](https://fal.ai/docs/documentation/development/docker-templates.md): Production-ready Dockerfile templates and optimization tips for fal Serverless. - [Download Model Weights and Files](https://fal.ai/docs/documentation/development/download-model-weights-and-files.md): Download model weights, datasets, and external files to your runner using fal toolkit utilities and Hugging Face best practices. - [Define Your Endpoints](https://fal.ai/docs/documentation/development/endpoints-overview.md): How to define, structure, and configure the API endpoints your fal App exposes to callers. - [Environment Variables](https://fal.ai/docs/documentation/development/environment-variables.md): Built-in environment variables that fal injects into every runner, covering authentication, app identity, region, lifecycle state, and storage. - [fal Runtime](https://fal.ai/docs/documentation/development/fal-runtime.md): How to use fal's managed Python runtime to run your models. - [Deploy Your First Image Generator](https://fal.ai/docs/documentation/development/getting-started/deploy-your-first-image-generator.md): Deploy a text-to-image AI model in under 5 minutes. This tutorial walks you through creating your own image generation API using Stable Diffusion XL. - [Installation & Setup](https://fal.ai/docs/documentation/development/getting-started/installation.md): Complete setup guide for the fal CLI and development environment. This guide covers all platforms and authentication methods. - [Quick Start - Hello World](https://fal.ai/docs/documentation/development/getting-started/quick-start.md): Deploy your first fal app in under 2 minutes. Learn the basics with a simple Hello World example. - [Handle Request Cancellations](https://fal.ai/docs/documentation/development/handle-cancellations.md): Handle in-flight request cancellations to free GPU resources when callers cancel queued or processing requests. - [Handle Inputs and Outputs](https://fal.ai/docs/documentation/development/handle-inputs-and-outputs.md): Define input and output schemas for your fal App endpoints that render correctly in the Playground. - [Import Code](https://fal.ai/docs/documentation/development/import-code.md): Bring local Python modules, files, and external repositories into your fal app's remote environment. - [Logging](https://fal.ai/docs/documentation/development/logging.md): Understand how logs are captured, scoped, and surfaced across runner logs, request logs, and the Playground. - [Secrets](https://fal.ai/docs/documentation/development/manage-secrets-securely.md): Store API keys, credentials, and other sensitive configuration securely, accessible to your fal App at runtime. - [Migrate an External Docker Server](https://fal.ai/docs/documentation/development/migrate-external-docker-server.md): Deploy an existing Docker-based server (ComfyUI, custom APIs) to fal's serverless platform. - [Migrate from Modal](https://fal.ai/docs/documentation/development/migrate-from-modal.md): A guide for migrating your Modal applications to fal. - [Migrate from Replicate](https://fal.ai/docs/documentation/development/migrate-from-replicate.md): A guide for migrating your Replicate Cog models to fal. - [Migrate from RunPod](https://fal.ai/docs/documentation/development/migrate-from-runpod.md): A guide for migrating your RunPod Serverless workers to fal. - [Migrating to fal](https://fal.ai/docs/documentation/development/migrating-to-fal.md): Bring your existing models and infrastructure to fal with minimal code changes. - [Multi-App Routing](https://fal.ai/docs/documentation/development/multi-app-routing.md): Use a lightweight proxy app to route requests between multiple fal apps based on input characteristics. - [Private Docker Registries](https://fal.ai/docs/documentation/development/private-registries.md): How to authenticate with private registries like Docker Hub, Google Artifact Registry, and AWS ECR. - [Realtime Endpoints](https://fal.ai/docs/documentation/development/realtime.md): Build low-latency, bidirectional WebSocket endpoints for interactive applications that require persistent connections and back-to-back requests. - [Request Headers](https://fal.ai/docs/documentation/development/request-headers.md): Access request headers in your fal App for logging, tracing, and per-request logic. - [Streaming Endpoints](https://fal.ai/docs/documentation/development/streaming.md): Stream progressive results to clients using Server-Sent Events (SSE) for real-time feedback during long-running operations. - [Test Models and Endpoints](https://fal.ai/docs/documentation/development/test-models-and-endpoints.md): Test your fal App endpoints programmatically using AppClient, which deploys an ephemeral instance and runs your tests against live infrastructure. - [Use a Custom Container Image](https://fal.ai/docs/documentation/development/use-custom-container-image.md): Bring your own Dockerfile to fal for full control over system packages, CUDA versions, and base images. - [Use KV Store](https://fal.ai/docs/documentation/development/use-kv-store.md): KVStore is a simple key-value storage for sharing state across serverless runners with zero setup required. - [Persistent Storage](https://fal.ai/docs/documentation/development/use-persistent-storage.md): Store model weights, datasets, and files on the shared /data volume that persists across runners and deployments. - [World Model Accelerator (WMA)](https://fal.ai/docs/documentation/development/wma.md): Experimental fal primitive for interactive world models over a peer-to-peer WebRTC stream between your runners and end users. - [Working with Files](https://fal.ai/docs/documentation/development/working-with-files.md): Download input files and return generated outputs from your fal App using the toolkit's file types and download utilities. - [Documentation](https://fal.ai/docs/documentation/index.md): Learn how to build and deploy AI applications with fal - [Platform Headers](https://fal.ai/docs/documentation/model-apis/common-parameters.md): HTTP headers that control request behavior across all inference methods on fal. - [Concurrency Limits](https://fal.ai/docs/documentation/model-apis/concurrency-limits.md): Understand and manage how many requests you can run simultaneously on fal. - [Model Errors](https://fal.ai/docs/documentation/model-apis/errors.md): Validation and content errors returned by models when inputs don't meet requirements. - [fal CDN](https://fal.ai/docs/documentation/model-apis/fal-cdn.md): Upload files to fal's CDN to use as inputs when calling models. - [FAQ](https://fal.ai/docs/documentation/model-apis/faq.md) - [Client Setup](https://fal.ai/docs/documentation/model-apis/inference/client-setup.md): Install and configure the fal client library - [Inference Methods](https://fal.ai/docs/documentation/model-apis/inference/index.md): Learn the different ways to call models on fal - [Proxy Setup](https://fal.ai/docs/documentation/model-apis/inference/proxy-setup.md): Keep your API key secure in client-side applications - [Asynchronous Inference](https://fal.ai/docs/documentation/model-apis/inference/queue.md): The recommended way to call models on fal - [Real-Time Inference](https://fal.ai/docs/documentation/model-apis/inference/real-time.md): WebSocket-based inference for ultra-low latency applications - [Reliability](https://fal.ai/docs/documentation/model-apis/inference/reliability.md): How fal ensures high reliability for your API requests through queueing, automatic retries, and model fallbacks. - [Streaming Inference](https://fal.ai/docs/documentation/model-apis/inference/streaming.md): Get progressive output as it's generated - [Synchronous Inference](https://fal.ai/docs/documentation/model-apis/inference/synchronous.md): A convenience wrapper for simple blocking calls - [Webhooks](https://fal.ai/docs/documentation/model-apis/inference/webhooks.md): Webhooks work in tandem with the queue system explained above, it is another way to interact with our queue. By providing us a webhook endpoint you get notified when the request is done as opposed to polling it. - [Data Retention & Storage](https://fal.ai/docs/documentation/model-apis/media-expiration.md): How fal stores your request data and generated media, and how to control retention. - [Common Model Arguments](https://fal.ai/docs/documentation/model-apis/model-arguments.md): Input parameters like seed, image_size, and safety checker that appear across many models on fal. - [Model APIs](https://fal.ai/docs/documentation/model-apis/overview.md): Access 1,000+ production-ready AI models through simple API calls - [Playground](https://fal.ai/docs/documentation/model-apis/playground.md): Test any model with real inputs, see results, and copy working code. - [Pricing](https://fal.ai/docs/documentation/model-apis/pricing.md): How billing works for fal Model APIs. - [Request Error Types](https://fal.ai/docs/documentation/model-apis/request-errors.md): Infrastructure-level error types for timeouts, runner failures, and connection errors. - [Sandbox](https://fal.ai/docs/documentation/model-apis/sandbox.md): Sandbox is your creative playground for testing and comparing the latest AI models across all popular media generation operations. Compare models side-by-side, estimate costs before running, and share your creations. - [Support](https://fal.ai/docs/documentation/model-apis/support.md): Support documentation for fal.ai AI APIs. Developer guide with examples, best practices, and implementation details. - [Workflow Endpoints](https://fal.ai/docs/documentation/model-apis/workflows.md): Workflows are a way to chain multiple models together to create a more complex pipeline. This allows you to create a single endpoint that can take an input and pass it through multiple models in sequence. This is useful for creating more complex models that require multiple steps, or for creating a… - [Model Access Controls](https://fal.ai/docs/documentation/organizations/access-controls.md): Restrict which models your team members can access via the API and Playground. - [Organizations](https://fal.ai/docs/documentation/organizations/index.md): Centralized management for teams, billing, and model access across your company. - [Managing Teams](https://fal.ai/docs/documentation/organizations/managing-teams.md): Control team lifecycle, member management, and organization-wide policies. - [Quick Start](https://fal.ai/docs/documentation/quickstart.md): Get started with fal in minutes - [API Reference](https://fal.ai/docs/documentation/serverless/distributed/api-reference.md): Essential API reference for fal.distributed: the key methods you need to build multi-GPU applications - [Overview](https://fal.ai/docs/documentation/serverless/distributed/overview.md): Learn how to leverage multiple GPUs for faster inference and training with fal.distributed - [Event Streaming](https://fal.ai/docs/documentation/serverless/distributed/streaming.md): Learn how to stream real-time results during distributed inference and training - [FAQ](https://fal.ai/docs/documentation/serverless/faq.md) - [Introduction to Serverless](https://fal.ai/docs/documentation/serverless/index.md): Deploy custom AI models on GPU infrastructure that autoscales from zero to thousands of machines. - [App Analytics](https://fal.ai/docs/documentation/serverless/observability/app-analytics.md): Monitor your application's performance with real-time metrics and detailed analytics. - [App Events](https://fal.ai/docs/documentation/serverless/observability/app-events.md): Track deployments, runner lifecycle, and config changes with a full audit trail. - [Error Analytics](https://fal.ai/docs/documentation/serverless/observability/error-analytics.md): Explore, filter, and debug request errors across your applications. - [Exporting Metrics](https://fal.ai/docs/documentation/serverless/observability/exporting-metrics.md): Export Prometheus-compatible metrics to Grafana, Datadog, or any monitoring tool. - [Log Drains](https://fal.ai/docs/documentation/serverless/observability/log-drains.md): Forward your application logs to external services like Datadog, Splunk, or Elasticsearch. - [Observability Overview](https://fal.ai/docs/documentation/serverless/observability/monitor-performance.md): Monitor your fal applications using the dashboard, CLI, and programmatic integrations. - [Cross-Service Tracing](https://fal.ai/docs/documentation/serverless/observability/opentelemetry-cross-service.md): Propagate trace context between two fal apps so that preprocessing and inference appear as children of a single parent trace - [OpenTelemetry in Production](https://fal.ai/docs/documentation/serverless/observability/opentelemetry-production.md): Configure sampling, batch export tuning, and graceful flush so your traces hold up under production load - [Custom Traces with OpenTelemetry](https://fal.ai/docs/documentation/serverless/observability/opentelemetry-traces.md): Add OpenTelemetry spans to your fal app to trace inference stages like warmup, diffusion, and image upload - [Slack Notifications](https://fal.ai/docs/documentation/serverless/observability/slack-notifications.md): Receive real-time alerts in Slack when your apps fail to start. - [Adjust Scaling Parameters](https://fal.ai/docs/documentation/serverless/optimizations/cold-start-scaling.md): Reduce cold starts by keeping warm runners available. - [FlashPack](https://fal.ai/docs/documentation/serverless/optimizations/flashpack.md): High-throughput tensor loading for PyTorch -- load models at up to 25Gbps without GDS. - [Optimizing Cold Starts](https://fal.ai/docs/documentation/serverless/optimizations/optimize-cold-starts.md): Understanding cold starts and how to reduce them. - [Optimize Container Images](https://fal.ai/docs/documentation/serverless/optimizations/optimize-container-images.md): Container optimization is key to achieving faster cold starts, reducing deployment sizes, and improving overall application performance. This guide covers Dockerfile optimization techniques, layer caching strategies, multi-stage builds, and build performance improvements to help you create efficient… - [Optimize Startup with Compiled Caches](https://fal.ai/docs/documentation/serverless/optimizations/optimize-startup-with-compiled-caches.md): Reduce cold-start time for compiled PyTorch models by sharing Inductor caches across workers. - [Optimizing Costs](https://fal.ai/docs/documentation/serverless/optimizations/optimizing-costs.md) - [Parallel File Loading](https://fal.ai/docs/documentation/serverless/optimizations/parallel-file-loading.md): Speed up model loading by pre-reading files in parallel from /data. - [Pricing](https://fal.ai/docs/documentation/serverless/pricing.md): How billing works for fal Serverless. - [Publishing to the Marketplace](https://fal.ai/docs/documentation/serverless/publishing-to-marketplace.md): Make your serverless app available on the fal Marketplace so anyone can call it with their own API key. - [GPU Health](https://fal.ai/docs/documentation/serverless/reliability/gpu-health.md): How fal monitors GPU health, detects failures, and gives you control over runner health through custom health checks. - [Retries and Error Handling](https://fal.ai/docs/documentation/serverless/reliability/retries.md): How fal retries failed requests, what each status code does to runners, and how to control behavior with response headers. - [Accounts and Identity](https://fal.ai/docs/documentation/setting-up/accounts-and-identity.md): Set up your fal account, choose between personal and team workspaces, and understand how identity works on the platform. - [Get Your API Key](https://fal.ai/docs/documentation/setting-up/authentication/index.md): Create an API key to authenticate your requests to fal - [AI Tools](https://fal.ai/docs/documentation/setting-up/mcp.md): Connect AI coding assistants to fal's 1,000+ models via the Model Context Protocol - [Libraries, APIs, and Community](https://fal.ai/docs/documentation/setting-up/resources.md): Client libraries, open-source packages, API references, and community links for building with fal. - [Teams](https://fal.ai/docs/documentation/setting-up/teams.md): Create shared workspaces with their own API keys, deployments, and billing. Manage members, roles, and understand how request attribution works. - [Why fal?](https://fal.ai/docs/documentation/why-fal.md): Industry-leading inference speed for generative AI, trusted by top AI applications - [Convert Speech to Text Tutorial](https://fal.ai/docs/examples/audio-speech/convert-speech-to-text.md) - [Deploy a Text-to-Music Model](https://fal.ai/docs/examples/audio-speech/deploy-text-to-music-model.md): This example demonstrates how to build a sophisticated text-to-music generation service using DiffRhythm, showcasing advanced fal features including custom Docker images, repository cloning, file downloading, and complex audio processing workflows. - [Deploy a Text-to-Speech Model](https://fal.ai/docs/examples/audio-speech/deploy-text-to-speech-model.md): This example demonstrates how to build a comprehensive text-to-speech service using Kokoro, showcasing CPU-efficient deployment, multi-language support, multiple endpoints with shared logic, and advanced audio processing techniques. - [Deploy Models with Custom Containers](https://fal.ai/docs/examples/deploy-models-with-custom-containers.md): fal now supports running apps within custom Docker containers, providing greater flexibility and control over your environment. - [Deploy a ComfyUI SDXL Turbo App](https://fal.ai/docs/examples/image-generation/deploy-comfyui-server.md): Build a serverless image generation API using ComfyUI and SDXL Turbo on fal. - [Deploy a Text-to-Image Model](https://fal.ai/docs/examples/image-generation/deploy-text-to-image-model.md) - [Deploy WAN LoRA Training](https://fal.ai/docs/examples/image-generation/deploy-wan-lora-training.md): Fine-tune WAN (text-to-video) with LoRA using your own short clips and images. - [Fastest FLUX Endpoint](https://fal.ai/docs/examples/image-generation/fast-flux.md): We believe fal has the fastest FLUX endpoint in the planet. If you can find a faster one, we guarantee to beat it within one week. 🤝 - [Fastest SDXL Endpoint](https://fal.ai/docs/examples/image-generation/fast-sdxl.md): We believe fal has the fastest SDXL endpoint in the planet. If you can find a faster one, we guarantee to beat it within one week. 🤝 - [Generate Images from Text Tutorial](https://fal.ai/docs/examples/image-generation/generate-images-from-text.md) - [Deploy ComfyUI on fal — Visual Control](https://fal.ai/docs/examples/image-generation/run-comfyui-visual.md): Edit ComfyUI workflows visually from your laptop with a fal-hosted GPU backend. Two zips, double-click, no code. - [Examples](https://fal.ai/docs/examples/index.md): Step-by-step tutorials and code examples for building with fal - [Custom Workflow UI Tutorial](https://fal.ai/docs/examples/integrations/custom-workflow-ui.md) - [Migrate an External Docker Server](https://fal.ai/docs/examples/integrations/migrate-external-docker-server.md): Deploy an existing Docker-based server (ComfyUI, custom APIs) to fal's serverless platform. - [Migrate from Modal](https://fal.ai/docs/examples/integrations/migrate-from-modal.md): A guide for migrating your Modal applications to fal. - [Migrate from Replicate](https://fal.ai/docs/examples/integrations/migrate-from-replicate.md): This guide will help you transition from using [Replicate](https://replicate.com/)'s tools, specifically their [Cog](https://github.com/replicate/cog) tool, to fal's platform. Cog is a tool used to package machine learning models in Docker containers, which simplifies the deployment process. - [Migrate from RunPod](https://fal.ai/docs/examples/integrations/migrate-from-runpod.md): A guide for migrating your RunPod Serverless workers to fal. - [Using fal within an n8n workflow](https://fal.ai/docs/examples/integrations/n8n.md): This guide will demonstrate, step-by-step, how to use fal within an n8n workflow. - [Add fal.ai to your Next.js app Integration](https://fal.ai/docs/examples/integrations/nextjs.md) - [Use LLMs Tutorial](https://fal.ai/docs/examples/integrations/use-llms.md): fal provides an easy-to-use API for generating text using Language Models (LLMs). You can use the `fal-ai/any-llm` endpoint to generate text based on a given prompt and model. - [Add fal.ai to your Next.js app Integration](https://fal.ai/docs/examples/integrations/vercel.md) - [Publish Custom Metrics with Prometheus Pushgateway](https://fal.ai/docs/examples/serverless/deploy-prometheus-pushgateway.md): Publish custom metrics on fal using Prometheus Pushgateway with direct port exposure and persistent storage. - [Deploy 3D Progressive Rendering](https://fal.ai/docs/examples/video-generation/deploy-3d-progressive-rendering.md): Build a real-time text-to-3D and image-to-3D application with live voxel streaming using SAM-3D Objects. - [Deploy Multi-GPU Inference](https://fal.ai/docs/examples/video-generation/deploy-multi-gpu-inference.md): Learn how to build a multi-GPU image generation service using data parallelism with Stable Diffusion XL, including real-time streaming and distributed worker coordination. - [Deploy Real-time Video-to-Video Model](https://fal.ai/docs/examples/video-generation/deploy-realtime-video-to-video-model.md): Run a real-time video-to-video pipeline that returns YOLO detections on your stream. - [Deploy Real-time World Model](https://fal.ai/docs/examples/video-generation/deploy-realtime-world-model.md): Run a real-time world model demo powered by Matrix-Game. - [Deploy a Text-to-Video Model](https://fal.ai/docs/examples/video-generation/deploy-text-to-video-model.md): This example demonstrates how to build a sophisticated text-to-video generation service using Wan2.1, showcasing advanced techniques including custom safety checking with multiple AI models, prompt expansion using LLMs, video tensor processing, and comprehensive integration of multiple fal services… - [Generate Videos from Image Tutorial](https://fal.ai/docs/examples/video-generation/generate-videos-from-image.md) - [Hunyuan 3d V3.1 Part API](https://fal.ai/docs/model-api-reference/3d-api/hunyuan-3d-v3.1-part.md): API reference for Hunyuan 3d V3.1 Part. Split 3D models into parts with Hunyuan 3D - [Hunyuan 3d V3.1 Pro API](https://fal.ai/docs/model-api-reference/3d-api/hunyuan-3d-v3.1-pro.md): API reference for Hunyuan 3d V3.1 Pro. Generate 3D models from images with Hunyuan 3D Pro - [Hunyuan 3d V3.1 Rapid API](https://fal.ai/docs/model-api-reference/3d-api/hunyuan-3d-v3.1-rapid.md): API reference for Hunyuan 3d V3.1 Rapid. Rapidly generate 3D models from images using Hunyuan 3D. - [Hunyuan 3d V3.1 Smart Topology API](https://fal.ai/docs/model-api-reference/3d-api/hunyuan-3d-v3.1-smart-topology.md): API reference for Hunyuan 3d V3.1 Smart Topology. Optimize 3D mesh topology with Hunyuan 3D Smart Topology. - [3D API](https://fal.ai/docs/model-api-reference/3d-api/overview.md): 3D API reference. Generate 3D assets from text or images using AI models. - [Trellis API](https://fal.ai/docs/model-api-reference/3d-api/trellis.md): API reference for Trellis. Generate 3D models from your images using Trellis. A native 3D generative model enabling versatile and high-quality 3D asset creation. - [Trellis 2 API](https://fal.ai/docs/model-api-reference/3d-api/trellis-2.md): API reference for Trellis 2. Generate 3D models from your images using Trellis 2. A native 3D generative model enabling versatile and high-quality 3D asset creation. - [Kling Video Create Voice API](https://fal.ai/docs/model-api-reference/audio-api/kling-video-create-voice.md): API reference for Kling Video Create Voice. Create Voices to be used with Kling Models Voice Control - [Kling Video V1 API](https://fal.ai/docs/model-api-reference/audio-api/kling-video-v1.md): API reference for Kling Video V1. Generate speech from text prompts and different voices using the Kling TTS model, which leverages advanced AI techniques to create high-quality text-to-speech. - [Kling Video Video To Audio API](https://fal.ai/docs/model-api-reference/audio-api/kling-video-video-to-audio.md): API reference for Kling Video Video To Audio. Generate audio from input videos using Kling - [Audio API](https://fal.ai/docs/model-api-reference/audio-api/overview.md): Audio API reference. Models for audio processing including text-to-speech, speech-to-text, voice cloning, and music generation.. - [Whisper API](https://fal.ai/docs/model-api-reference/audio-api/whisper.md): API reference for Whisper. Whisper is a model for speech transcription and translation. - [Xai Tts API](https://fal.ai/docs/model-api-reference/audio-api/xai-tts.md): API reference for Xai Tts. Generate speech with expressive and realistic voices from xAI - [Birefnet API](https://fal.ai/docs/model-api-reference/image-generation-api/birefnet.md): API reference for Birefnet. bilateral reference framework (BiRefNet) for high-resolution dichotomous image segmentation (DIS) - [Bria Background API](https://fal.ai/docs/model-api-reference/image-generation-api/bria-background.md): API reference for Bria Background. Bria RMBG 2.0 enables seamless removal of backgrounds from images, ideal for professional editing tasks. Trained exclusively on licensed data for safe and risk-free - [Bria Embed Product API](https://fal.ai/docs/model-api-reference/image-generation-api/bria-embed-product.md): API reference for Bria Embed Product. Seamlessly integrate one or more products into a predefined scene with pixel-perfect control. - [Bria Eraser API](https://fal.ai/docs/model-api-reference/image-generation-api/bria-eraser.md): API reference for Bria Eraser. Bria Eraser enables precise removal of unwanted objects from images while maintaining high-quality outputs. Trained exclusively on licensed data for safe and risk-free c - [Bria Expand API](https://fal.ai/docs/model-api-reference/image-generation-api/bria-expand.md): API reference for Bria Expand. Bria Expand expands images beyond their borders in high quality. Trained exclusively on licensed data for safe and risk-free commercial use. Access the model's source co - [Bria Fibo API](https://fal.ai/docs/model-api-reference/image-generation-api/bria-fibo.md): API reference for Bria Fibo. SOTA Open source model trained on licensed data, transforming intent into structured control for precise, high-quality AI image generation in enterprise and agentic workfl - [Bria Fibo Edit API](https://fal.ai/docs/model-api-reference/image-generation-api/bria-fibo-edit.md): API reference for Bria Fibo Edit. A high-quality editing model that achieves maximum controllability and transparency by combining JSON + Mask + Image. - [Bria Fibo Lite API](https://fal.ai/docs/model-api-reference/image-generation-api/bria-fibo-lite.md): API reference for Bria Fibo Lite. Fibo Lite, the new addition to the Fibo model family, allows generating high-quality images with the same controllability of the JSON structured prompt with significa - [Bria Genfill API](https://fal.ai/docs/model-api-reference/image-generation-api/bria-genfill.md): API reference for Bria Genfill. Bria GenFill enables high-quality object addition or visual transformation. Trained exclusively on licensed data for safe and risk-free commercial use. Access the model - [Bria Product Shot API](https://fal.ai/docs/model-api-reference/image-generation-api/bria-product-shot.md): API reference for Bria Product Shot. Place any product in any scenery with just a prompt or reference image while maintaining high integrity of the product. Trained exclusively on licensed data for sa - [Bria Reimagine API](https://fal.ai/docs/model-api-reference/image-generation-api/bria-reimagine.md): API reference for Bria Reimagine. Structure Reference allows generating new images while preserving the structure of an input image, guided by text prompts. Perfect for transforming sketches, illustra - [Bria Replace Background API](https://fal.ai/docs/model-api-reference/image-generation-api/bria-replace-background.md): API reference for Bria Replace Background. Creates enriched product shots by placing them in various environments using textual descriptions. - [Bria Text To Image API](https://fal.ai/docs/model-api-reference/image-generation-api/bria-text-to-image.md): API reference for Bria Text To Image. Bria's Text-to-Image model for HD images. Trained exclusively on licensed data for safe and risk-free commercial use. Available also as source code and weights. F - [Bytedance Dreamina V3.1 API](https://fal.ai/docs/model-api-reference/image-generation-api/bytedance-dreamina-v3.1.md): API reference for Bytedance Dreamina V3.1. Dreamina showcases superior picture effects, with significant improvements in picture aesthetics, precise and diverse styles, and rich details. - [Bytedance Seedream V3 API](https://fal.ai/docs/model-api-reference/image-generation-api/bytedance-seedream-v3.md): API reference for Bytedance Seedream V3. Seedream 3.0 is a bilingual (Chinese and English) text-to-image model that excels at text-to-image generation. - [Bytedance Seedream V4 API](https://fal.ai/docs/model-api-reference/image-generation-api/bytedance-seedream-v4.md): API reference for Bytedance Seedream V4. A new-generation image creation model ByteDance, Seedream 4.0 integrates image generation and image editing capabilities into a single, unified architecture. - [Bytedance Seedream V4.5 API](https://fal.ai/docs/model-api-reference/image-generation-api/bytedance-seedream-v4.5.md): API reference for Bytedance Seedream V4.5. A new-generation image creation model ByteDance, Seedream 4.5 integrates image generation and image editing capabilities into a single, unified architecture. - [Bytedance Seedream V5 Lite API](https://fal.ai/docs/model-api-reference/image-generation-api/bytedance-seedream-v5-lite.md): API reference for Bytedance Seedream V5 Lite. Image editing endpoint for the fast Lite version of Seedream 5.0, supporting high quality intelligent image editing with multiple inputs. - [Florence 2 Large API](https://fal.ai/docs/model-api-reference/image-generation-api/florence-2-large.md): API reference for Florence 2 Large. Florence-2 is an advanced vision foundation model that uses a prompt-based approach to handle a wide range of vision and vision-language tasks - [Flux 2 Pro API](https://fal.ai/docs/model-api-reference/image-generation-api/flux-2-pro.md): API reference for Flux 2 Pro. Image editing with FLUX.2 [pro] from Black Forest Labs. Ideal for high-quality image manipulation, style transfer, and sequential editing workflows - [Flux Dev API](https://fal.ai/docs/model-api-reference/image-generation-api/flux-dev.md): API reference for Flux Dev. FLUX.1 [dev] is a 12 billion parameter flow transformer that generates high-quality images from text. It is suitable for personal and commercial use. - [Flux Krea API](https://fal.ai/docs/model-api-reference/image-generation-api/flux-krea.md): API reference for Flux Krea. FLUX.1 Krea [dev] is a 12 billion parameter flow transformer that generates high-quality images from text with incredible aesthetics. It is suitable for personal and comme - [Flux Lora API](https://fal.ai/docs/model-api-reference/image-generation-api/flux-lora.md): API reference for Flux Lora. Super fast endpoint for the FLUX.1 [dev] model with LoRA support, enabling rapid and high-quality image generation using pre-trained LoRA adaptations for personalization, - [Flux Pro Kontext API](https://fal.ai/docs/model-api-reference/image-generation-api/flux-pro-kontext.md): API reference for Flux Pro Kontext. FLUX.1 Kontext [pro] handles both text and reference images as inputs, seamlessly enabling targeted, local edits and complex transformations of entire scenes. - [Flux Pro Kontext Max API](https://fal.ai/docs/model-api-reference/image-generation-api/flux-pro-kontext-max.md): API reference for Flux Pro Kontext Max. FLUX.1 Kontext [max] is a model with greatly improved prompt adherence and typography generation meet premium consistency for editing without compromise on spee - [Flux Pro Kontext Multi API](https://fal.ai/docs/model-api-reference/image-generation-api/flux-pro-kontext-multi.md): API reference for Flux Pro Kontext Multi. Experimental version of FLUX.1 Kontext [pro] with multi image handling capabilities - [Flux Pro Kontext Text To Image API](https://fal.ai/docs/model-api-reference/image-generation-api/flux-pro-kontext-text-to-image.md): API reference for Flux Pro Kontext Text To Image. The FLUX.1 Kontext [pro] text-to-image delivers state-of-the-art image generation results with unprecedented prompt following, photorealistic renderin - [Flux Pro V1 API](https://fal.ai/docs/model-api-reference/image-generation-api/flux-pro-v1.md): API reference for Flux Pro V1. FLUX.1 [pro] Fill is a high-performance endpoint for the FLUX.1 [pro] model that enables rapid transformation of existing images, delivering high-quality style transfers - [Flux Pro V1.1 API](https://fal.ai/docs/model-api-reference/image-generation-api/flux-pro-v1.1.md): API reference for Flux Pro V1.1. FLUX1.1 [pro] is an enhanced version of FLUX.1 [pro], improved image generation capabilities, delivering superior composition, detail, and artistic fidelity compared t - [Flux Pro V1.1 Ultra API](https://fal.ai/docs/model-api-reference/image-generation-api/flux-pro-v1.1-ultra.md): API reference for Flux Pro V1.1 Ultra. FLUX1.1 [pro] ultra is the newest version of FLUX1.1 [pro], maintaining professional-grade image quality while delivering up to 2K resolution with improved photo - [Flux Pro V1.1 Ultra Finetuned API](https://fal.ai/docs/model-api-reference/image-generation-api/flux-pro-v1.1-ultra-finetuned.md): API reference for Flux Pro V1.1 Ultra Finetuned. FLUX1.1 [pro] ultra fine-tuned is the newest version of FLUX1.1 [pro] with a fine-tuned LoRA, maintaining professional-grade image quality while delive - [Flux Schnell API](https://fal.ai/docs/model-api-reference/image-generation-api/flux-schnell.md): API reference for Flux Schnell. FLUX.1 [schnell] is a 12 billion parameter flow transformer that generates high-quality images from text in 1 to 4 steps, suitable for personal and commercial use. - [Flux Srpo API](https://fal.ai/docs/model-api-reference/image-generation-api/flux-srpo.md): API reference for Flux Srpo. FLUX.1 SRPO [dev] is a 12 billion parameter flow transformer that generates high-quality images from text with incredible aesthetics. It is suitable for personal and comme - [Gemini 3 Pro Image Preview API](https://fal.ai/docs/model-api-reference/image-generation-api/gemini-3-pro-image-preview.md): API reference for Gemini 3 Pro Image Preview. Gemini 3 Pro Image (a.k.a Nano Banana Pro) is Google's state-of-the-art high-fidelity image generation and editing model - [Gpt Image 1.5 API](https://fal.ai/docs/model-api-reference/image-generation-api/gpt-image-1.5.md): API reference for Gpt Image 1.5. GPT Image 1.5 generates high-fidelity images with strong prompt adherence, preserving composition, lighting, and fine-grained detail. - [Ideogram Character API](https://fal.ai/docs/model-api-reference/image-generation-api/ideogram-character.md): API reference for Ideogram Character. Generate consistent character appearances across multiple images. Maintain facial features, proportions, and distinctive traits for cohesive storytelling and bran - [Ideogram Upscale API](https://fal.ai/docs/model-api-reference/image-generation-api/ideogram-upscale.md): API reference for Ideogram Upscale. Ideogram Upscale enhances the resolution of the reference image by up to 2X and might enhance the reference image too. Optionally refine outputs with a prompt for g - [Ideogram V2 API](https://fal.ai/docs/model-api-reference/image-generation-api/ideogram-v2.md): API reference for Ideogram V2. Generate high-quality images, posters, and logos with Ideogram V2. Features exceptional typography handling and realistic outputs optimized for commercial and creative u - [Ideogram V2 Edit API](https://fal.ai/docs/model-api-reference/image-generation-api/ideogram-v2-edit.md): API reference for Ideogram V2 Edit. Transform existing images with Ideogram V2's editing capabilities. Modify, adjust, and refine images while maintaining high fidelity and realistic outputs with prec - [Ideogram V2 Remix API](https://fal.ai/docs/model-api-reference/image-generation-api/ideogram-v2-remix.md): API reference for Ideogram V2 Remix. Reimagine existing images with Ideogram V2's remix feature. Create variations and adaptations while preserving core elements and adding new creative directions thr - [Ideogram V2 Turbo API](https://fal.ai/docs/model-api-reference/image-generation-api/ideogram-v2-turbo.md): API reference for Ideogram V2 Turbo. Accelerated image generation with Ideogram V2 Turbo. Create high-quality visuals, posters, and logos with enhanced speed while maintaining Ideogram's signature qua - [Ideogram V2a API](https://fal.ai/docs/model-api-reference/image-generation-api/ideogram-v2a.md): API reference for Ideogram V2a. Generate high-quality images, posters, and logos with Ideogram V2A. Features exceptional typography handling and realistic outputs optimized for commercial and creative - [Ideogram V2a Remix API](https://fal.ai/docs/model-api-reference/image-generation-api/ideogram-v2a-remix.md): API reference for Ideogram V2a Remix. Create variations of existing images with Ideogram V2A Remix while maintaining creative control through prompt guidance. - [Ideogram V2a Turbo API](https://fal.ai/docs/model-api-reference/image-generation-api/ideogram-v2a-turbo.md): API reference for Ideogram V2a Turbo. Accelerated image generation with Ideogram V2A Turbo. Create high-quality visuals, posters, and logos with enhanced speed while maintaining Ideogram's signature q - [Ideogram V3 API](https://fal.ai/docs/model-api-reference/image-generation-api/ideogram-v3.md): API reference for Ideogram V3. Generate high-quality images, posters, and logos with Ideogram V3. Features exceptional typography handling and realistic outputs optimized for commercial and creative u - [Imageutils API](https://fal.ai/docs/model-api-reference/image-generation-api/imageutils.md): API reference for Imageutils. Remove the background from an image. - [Nano Banana API](https://fal.ai/docs/model-api-reference/image-generation-api/nano-banana.md): API reference for Nano Banana. Google's famous original image generation and editing model - [Nano Banana 2 API](https://fal.ai/docs/model-api-reference/image-generation-api/nano-banana-2.md): API reference for Nano Banana 2. Nano Banana 2 is Google's new state-of-the-art fast image generation and editing model - [Nano Banana Pro API](https://fal.ai/docs/model-api-reference/image-generation-api/nano-banana-pro.md): API reference for Nano Banana Pro. Nano Banana Pro is Google's new state-of-the-art image generation and editing model - [Image Generation API](https://fal.ai/docs/model-api-reference/image-generation-api/overview.md): Image Generation API reference. Generate and edit images using state-of-the-art diffusion and transformer models. - [Seedvr Upscale Image API](https://fal.ai/docs/model-api-reference/image-generation-api/seedvr-upscale-image.md): API reference for Seedvr Upscale Image. Use SeedVR2 to upscale your images - [Topaz Upscale API](https://fal.ai/docs/model-api-reference/image-generation-api/topaz-upscale.md): API reference for Topaz Upscale. Use the powerful and accurate topaz image enhancer to enhance your images. - [Xai Grok Imagine Image API](https://fal.ai/docs/model-api-reference/image-generation-api/xai-grok-imagine-image.md): API reference for Xai Grok Imagine Image. Generate highly aesthetic images with xAI's Grok Imagine Image generation model. - [Z Image Base API](https://fal.ai/docs/model-api-reference/image-generation-api/z-image-base.md): API reference for Z Image Base. Z-Image is the foundation model of the Z- Image family, engineered for good quality, robust generative diversity, broad stylistic coverage, and precise prompt adherence - [Z Image Turbo API](https://fal.ai/docs/model-api-reference/image-generation-api/z-image-turbo.md): API reference for Z Image Turbo. Z-Image Turbo is a super fast text-to-image model of 6B parameters developed by Tongyi-MAI. - [Z Image Turbo Controlnet API](https://fal.ai/docs/model-api-reference/image-generation-api/z-image-turbo-controlnet.md): API reference for Z Image Turbo Controlnet. Generate images from text and edge, depth or pose images using Z-Image Turbo, Tongyi-MAI's super-fast 6B model. - [Z Image Turbo Image To Image API](https://fal.ai/docs/model-api-reference/image-generation-api/z-image-turbo-image-to-image.md): API reference for Z Image Turbo Image To Image. Generate images from text and images using Z-Image Turbo, Tongyi-MAI's super-fast 6B model. - [Z Image Turbo Inpaint API](https://fal.ai/docs/model-api-reference/image-generation-api/z-image-turbo-inpaint.md): API reference for Z Image Turbo Inpaint. Generate images from text, an image and a mask using Z-Image Turbo, Tongyi-MAI's super-fast 6B model. - [Z Image Turbo Lora API](https://fal.ai/docs/model-api-reference/image-generation-api/z-image-turbo-lora.md): API reference for Z Image Turbo Lora. Text-to-Image endpoint with LoRA support for Z-Image Turbo, a super fast text-to-image model of 6B parameters developed by Tongyi-MAI. - [Z Image Turbo Tiling API](https://fal.ai/docs/model-api-reference/image-generation-api/z-image-turbo-tiling.md): API reference for Z Image Turbo Tiling. Generate seamlessly tiling photorealistic images from text using Z-Image Turbo - [Model API Reference](https://fal.ai/docs/model-api-reference/index.md): Complete API reference for fal.ai's image, video, audio, vision, and 3D generation models on fal.ai. - [Birefnet V2 API](https://fal.ai/docs/model-api-reference/video-generation-api/birefnet-v2.md): API reference for Birefnet V2. Video background removal version of bilateral reference framework (BiRefNet) for high-resolution dichotomous image segmentation (DIS) - [Bria Video API](https://fal.ai/docs/model-api-reference/video-generation-api/bria-video.md): API reference for Bria Video. Automatically remove backgrounds from videos -perfect for creating clean, professional content without a green screen. - [Bytedance Dreamactor API](https://fal.ai/docs/model-api-reference/video-generation-api/bytedance-dreamactor.md): API reference for Bytedance Dreamactor. Transfer motion from a video to characters in an image using Dreamactor v2. Great performance for non-human and multiple characters - [Bytedance Omnihuman API](https://fal.ai/docs/model-api-reference/video-generation-api/bytedance-omnihuman.md): API reference for Bytedance Omnihuman. OmniHuman generates video using an image of a human figure paired with an audio file. It produces vivid, high-quality videos where the character’s emotions and m - [Bytedance Seedance 2.0 Fast API](https://fal.ai/docs/model-api-reference/video-generation-api/bytedance-seedance-2.0-fast.md): API reference for Bytedance Seedance 2.0 Fast. ByteDance's most advanced text-to-video model, fast tier. Lower latency and cost with cinematic output, native audio, multi-shot editing, and director-le - [Bytedance Seedance 2.0 Image To Video API](https://fal.ai/docs/model-api-reference/video-generation-api/bytedance-seedance-2.0-image-to-video.md): API reference for Bytedance Seedance 2.0 Image To Video. ByteDance's most advanced image-to-video model. Animate still images into cinematic video with synchronized audio, start and end frame control, - [Bytedance Seedance 2.0 Reference To Video API](https://fal.ai/docs/model-api-reference/video-generation-api/bytedance-seedance-2.0-reference-to-video.md): API reference for Bytedance Seedance 2.0 Reference To Video. ByteDance's most advanced reference-to-video model. Generate video from up to 9 images, 3 videos, and 3 audio clips with native audio and c - [Bytedance Seedance 2.0 Text To Video API](https://fal.ai/docs/model-api-reference/video-generation-api/bytedance-seedance-2.0-text-to-video.md): API reference for Bytedance Seedance 2.0 Text To Video. ByteDance's most advanced text-to-video model. Cinematic output with native audio, multi-shot editing, real-world physics, and director-level ca - [Bytedance Seedance V1 Lite API](https://fal.ai/docs/model-api-reference/video-generation-api/bytedance-seedance-v1-lite.md): API reference for Bytedance Seedance V1 Lite. Seedance 1.0 Lite - [Bytedance Seedance V1 Pro Fast API](https://fal.ai/docs/model-api-reference/video-generation-api/bytedance-seedance-v1-pro-fast.md): API reference for Bytedance Seedance V1 Pro Fast. Image to Video endpoint for Seedance 1.0 Pro Fast, a next-generation video model designed to deliver maximum performance at minimal cost - [Bytedance Seedance V1 Pro Image To Video API](https://fal.ai/docs/model-api-reference/video-generation-api/bytedance-seedance-v1-pro-image-to-video.md): API reference for Bytedance Seedance V1 Pro Image To Video. Seedance 1.0 Pro, a high quality video generation model developed by Bytedance. - [Bytedance Seedance V1 Pro Text To Video API](https://fal.ai/docs/model-api-reference/video-generation-api/bytedance-seedance-v1-pro-text-to-video.md): API reference for Bytedance Seedance V1 Pro Text To Video. Seedance 1.0 Pro, a high quality video generation model developed by Bytedance. - [Bytedance Seedance V1.5 Pro API](https://fal.ai/docs/model-api-reference/video-generation-api/bytedance-seedance-v1.5-pro.md): API reference for Bytedance Seedance V1.5 Pro. Generate videos with audio with Seedance 1.5 (supports start & end frame) - [Bytedance Video Stylize API](https://fal.ai/docs/model-api-reference/video-generation-api/bytedance-video-stylize.md): API reference for Bytedance Video Stylize. Transform your images into stylized videos using this workflow. - [Kling Video Ai Avatar V2 API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-ai-avatar-v2.md): API reference for Kling Video Ai Avatar V2. Kling AI Avatar v2 Pro: The premium endpoint for creating avatar videos with realistic humans, animals, cartoons, or stylized characters - [Kling Video Lipsync API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-lipsync.md): API reference for Kling Video Lipsync. Kling LipSync is an audio-to-video model that generates realistic lip movements from audio input. - [Kling Video O1 Image To Video API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-o1-image-to-video.md): API reference for Kling Video O1 Image To Video. Generate a video by taking a start frame and an end frame, animating the transition between them while following text-driven style and scene guidance. - [Kling Video O1 Reference To Video API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-o1-reference-to-video.md): API reference for Kling Video O1 Reference To Video. Transform images, elements, and text into consistent, high-quality video scenes, ensuring stable character identity, object details, and environmen - [Kling Video O1 Standard Image To Video API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-o1-standard-image-to-video.md): API reference for Kling Video O1 Standard Image To Video. Generate a video by taking a start frame and an end frame, animating the transition between them while following text-driven style and scene g - [Kling Video O1 Standard Reference To Video API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-o1-standard-reference-to-video.md): API reference for Kling Video O1 Standard Reference To Video. Transform images, elements, and text into consistent, high-quality video scenes, ensuring stable character identity, object details, and e - [Kling Video O1 Standard Video To Video API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-o1-standard-video-to-video.md): API reference for Kling Video O1 Standard Video To Video. Edit an existing video using natural-language instructions, transforming subjects, settings, and style while retaining the original motion str - [Kling Video O1 Video To Video API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-o1-video-to-video.md): API reference for Kling Video O1 Video To Video. Edit an existing video using natural-language instructions, transforming subjects, settings, and style while retaining the original motion structure. - [Kling Video O3 Pro Image To Video API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-o3-pro-image-to-video.md): API reference for Kling Video O3 Pro Image To Video. Generate a video by taking a start frame and an end frame, animating the transition between them while following text-driven style and scene guidan - [Kling Video O3 Pro Reference To Video API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-o3-pro-reference-to-video.md): API reference for Kling Video O3 Pro Reference To Video. Transform images, elements, and text into consistent, high-quality video scenes, ensuring stable character identity, object details, and enviro - [Kling Video O3 Pro Text To Video API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-o3-pro-text-to-video.md): API reference for Kling Video O3 Pro Text To Video. Generate realistic videos using Kling O3 from Kling Team! - [Kling Video O3 Pro Video To Video API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-o3-pro-video-to-video.md): API reference for Kling Video O3 Pro Video To Video. Edit videos using Kling O3 from Kling Team! - [Kling Video O3 Standard Image To Video API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-o3-standard-image-to-video.md): API reference for Kling Video O3 Standard Image To Video. Generate a video by taking a start frame and an end frame, animating the transition between them while following text-driven style and scene g - [Kling Video O3 Standard Reference To Video API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-o3-standard-reference-to-video.md): API reference for Kling Video O3 Standard Reference To Video. Transform images, elements, and text into consistent, high-quality video scenes, ensuring stable character identity, object details, and e - [Kling Video O3 Standard Text To Video API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-o3-standard-text-to-video.md): API reference for Kling Video O3 Standard Text To Video. Generate realistic videos using Kling O3 from Kling Team! - [Kling Video O3 Standard Video To Video API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-o3-standard-video-to-video.md): API reference for Kling Video O3 Standard Video To Video. Edit videos using Kling O3 from Kling Team! - [Kling Video V1 Pro API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-v1-pro.md): API reference for Kling Video V1 Pro. Kling AI Avatar Pro: The premium endpoint for creating avatar videos with realistic humans, animals, cartoons, or stylized characters - [Kling Video V1 Standard API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-v1-standard.md): API reference for Kling Video V1 Standard. Generate video clips from your images using Kling 1.0 - [Kling Video V1.5 Pro API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-v1.5-pro.md): API reference for Kling Video V1.5 Pro. Generate video clips from your images using Kling 1.5 (pro) - [Kling Video V1.6 Pro API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-v1.6-pro.md): API reference for Kling Video V1.6 Pro. Generate video clips from your images using Kling 1.6 (pro) - [Kling Video V1.6 Standard API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-v1.6-standard.md): API reference for Kling Video V1.6 Standard. Generate video clips from your images using Kling 1.6 (std) - [Kling Video V2 Master API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-v2-master.md): API reference for Kling Video V2 Master. Generate video clips from your images using Kling 2.0 Master - [Kling Video V2.1 Master API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-v2.1-master.md): API reference for Kling Video V2.1 Master. Kling 2.1 Master: The premium endpoint for Kling 2.1, designed for top-tier image-to-video generation with unparalleled motion fluidity, cinematic visuals, a - [Kling Video V2.1 Pro API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-v2.1-pro.md): API reference for Kling Video V2.1 Pro. Kling 2.1 Pro is an advanced endpoint for the Kling 2.1 model, offering professional-grade videos with enhanced visual fidelity, precise camera movements, and d - [Kling Video V2.1 Standard API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-v2.1-standard.md): API reference for Kling Video V2.1 Standard. Kling 2.1 Standard is a cost-efficient endpoint for the Kling 2.1 model, delivering high-quality image-to-video generation - [Kling Video V2.5 Turbo Pro API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-v2.5-turbo-pro.md): API reference for Kling Video V2.5 Turbo Pro. Kling 2.5 Turbo Pro: Top-tier image-to-video generation with unparalleled motion fluidity, cinematic visuals, and exceptional prompt precision. - [Kling Video V2.5 Turbo Standard API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-v2.5-turbo-standard.md): API reference for Kling Video V2.5 Turbo Standard. Kling 2.5 Turbo Standard: Top-tier image-to-video generation with unparalleled motion fluidity, cinematic visuals, and exceptional prompt precision. - [Kling Video V2.6 Pro API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-v2.6-pro.md): API reference for Kling Video V2.6 Pro. Kling 2.6 Pro: Top-tier image-to-video with cinematic visuals, fluid motion, and native audio generation. - [Kling Video V2.6 Standard API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-v2.6-standard.md): API reference for Kling Video V2.6 Standard. Transfer movements from a reference video to any character image. Cost-effective mode for motion transfer, perfect for portraits and simple animations. - [Kling Video V3 Pro API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-v3-pro.md): API reference for Kling Video V3 Pro. Kling 3.0 Pro: Top-tier text-to-video with cinematic visuals, fluid motion, and native audio generation, with multi-shot support. - [Kling Video V3 Standard API](https://fal.ai/docs/model-api-reference/video-generation-api/kling-video-v3-standard.md): API reference for Kling Video V3 Standard. Kling 3.0 Standard: Top-tier image-to-video with cinematic visuals, fluid motion, and native audio generation, with custom element support. - [Video Generation API](https://fal.ai/docs/model-api-reference/video-generation-api/overview.md): Video Generation API reference. Generate videos from text prompts or images using cutting-edge video generation models. - [Seedvr Upscale API](https://fal.ai/docs/model-api-reference/video-generation-api/seedvr-upscale.md): API reference for Seedvr Upscale. Upscale your videos using SeedVR2 with temporal consistency! - [Sora 2 Characters API](https://fal.ai/docs/model-api-reference/video-generation-api/sora-2-characters.md): API reference for Sora 2 Characters. Generate character ids to use with Sora 2 generations - [Sora 2 Image To Video API](https://fal.ai/docs/model-api-reference/video-generation-api/sora-2-image-to-video.md): API reference for Sora 2 Image To Video. Image-to-video endpoint for Sora 2, OpenAI's state-of-the-art video model capable of creating richly detailed, dynamic clips with audio from natural language o - [Sora 2 Text To Video API](https://fal.ai/docs/model-api-reference/video-generation-api/sora-2-text-to-video.md): API reference for Sora 2 Text To Video. Text-to-video endpoint for Sora 2, OpenAI's state-of-the-art video model capable of creating richly detailed, dynamic clips with audio from natural language or - [Sora 2 Video To Video API](https://fal.ai/docs/model-api-reference/video-generation-api/sora-2-video-to-video.md): API reference for Sora 2 Video To Video. Video-to-video remix endpoint for Sora 2, OpenAI’s advanced model that transforms existing videos based on new text or image prompts allowing rich edits, style - [Topaz Upscale API](https://fal.ai/docs/model-api-reference/video-generation-api/topaz-upscale.md): API reference for Topaz Upscale. Professional-grade video upscaling using Topaz technology. Enhance your videos with high-quality upscaling. - [Veo3.1 API](https://fal.ai/docs/model-api-reference/video-generation-api/veo3.1.md): API reference for Veo3.1. Veo 3.1 by Google, the most advanced AI video generation model in the world. With sound on! - [Veo3.1 Extend Video API](https://fal.ai/docs/model-api-reference/video-generation-api/veo3.1-extend-video.md): API reference for Veo3.1 Extend Video. Extend Veo-Created Videos up to 30 seconds - [Veo3.1 Fast API](https://fal.ai/docs/model-api-reference/video-generation-api/veo3.1-fast.md): API reference for Veo3.1 Fast. Faster and more cost effective version of Google's Veo 3.1! - [Veo3.1 First Last Frame To Video API](https://fal.ai/docs/model-api-reference/video-generation-api/veo3.1-first-last-frame-to-video.md): API reference for Veo3.1 First Last Frame To Video. Generate videos from a first and last framed using Google's Veo 3.1 - [Veo3.1 Image To Video API](https://fal.ai/docs/model-api-reference/video-generation-api/veo3.1-image-to-video.md): API reference for Veo3.1 Image To Video. Veo 3.1 is the latest state-of-the art video generation model from Google DeepMind - [Veo3.1 Lite API](https://fal.ai/docs/model-api-reference/video-generation-api/veo3.1-lite.md): API reference for Veo3.1 Lite. Veo 3.1 Lite balances practical utility with professional capabilities, supporting Text-to-Video and Image-to-Video - [Veo3.1 Reference To Video API](https://fal.ai/docs/model-api-reference/video-generation-api/veo3.1-reference-to-video.md): API reference for Veo3.1 Reference To Video. Generate Videos from images using Google's Veo 3.1 - [Xai Grok Imagine Video API](https://fal.ai/docs/model-api-reference/video-generation-api/xai-grok-imagine-video.md): API reference for Xai Grok Imagine Video. Generate videos from images with audio using xAI's Grok Imagine Video model. - [Florence 2 Large API](https://fal.ai/docs/model-api-reference/vision-api/florence-2-large.md): API reference for Florence 2 Large. Florence-2 is an advanced vision foundation model that uses a prompt-based approach to handle a wide range of vision and vision-language tasks - [Imageutils API](https://fal.ai/docs/model-api-reference/vision-api/imageutils.md): API reference for Imageutils. Predict the probability of an image being NSFW. - [Openrouter Router API](https://fal.ai/docs/model-api-reference/vision-api/openrouter-router.md): API reference for Openrouter Router. Run any Vision Language Model with fal. Analyze and understand images using Claude (Anthropic), GPT-5 / GPT-4o (OpenAI), Gemini (Google), Grok (xAI), Llama (Meta), - [Vision API](https://fal.ai/docs/model-api-reference/vision-api/overview.md): Vision API reference. Models for understanding and analyzing images, including captioning, visual question answering, and object detection.. - [Account Billing](https://fal.ai/docs/platform-apis/v1/account/billing.md): Returns billing information for the authenticated account. Use the `expand` parameter to include additional details. - [FOCUS Report](https://fal.ai/docs/platform-apis/v1/account/focus.md): Returns a FOCUS compliant billing report as a CSV download. - [Model Access Controls Report](https://fal.ai/docs/platform-apis/v1/account/model-access-controls.md): Returns the current model access controls for your organization as a CSV download. - [Create Compute Instance](https://fal.ai/docs/platform-apis/v1/compute/instances/create.md): Creates a new compute instance with the specified configuration and SSH key. - [Delete Compute Instance](https://fal.ai/docs/platform-apis/v1/compute/instances/delete.md): Deletes a specific compute instance by its ID. This action is irreversible. - [Get Compute Instance](https://fal.ai/docs/platform-apis/v1/compute/instances/get.md): Retrieves detailed information about a specific compute instance by its ID. - [List Compute Instances](https://fal.ai/docs/platform-apis/v1/compute/instances/list.md): Returns a list of all compute instances belonging to the authenticated user's workspace. - [Create API Key](https://fal.ai/docs/platform-apis/v1/keys/create.md): Creates a new API key with the specified alias. - [Delete API Key](https://fal.ai/docs/platform-apis/v1/keys/delete.md): Deletes an API key by its ID. This action is irreversible. - [List API Keys](https://fal.ai/docs/platform-apis/v1/keys/list.md): Returns a list of all API keys belonging to the authenticated user's workspace. - [Model search](https://fal.ai/docs/platform-apis/v1/models.md): Unified endpoint for discovering model endpoints. Supports three usage modes: - [Analytics](https://fal.ai/docs/platform-apis/v1/models/analytics.md): Time-bucketed metrics per model endpoint, including request counts, success/error rates, and latency percentiles. `prepare_duration` reflects queue/prepare time before execution; `duration` is request execution time. Use with the Queue/Webhooks flow to monitor SLAs. - [Pricing](https://fal.ai/docs/platform-apis/v1/models/pricing.md): Returns unit pricing for requested endpoint IDs. Most models use **output-based** pricing (e.g., per image/video with proportional adjustments for resolution/length). Some models use **GPU-based** pricing depending on architecture. Values are expressed per model's billing unit in a given currency. - [Estimate cost](https://fal.ai/docs/platform-apis/v1/models/pricing/estimate.md): Computes cost estimates using one of two methods: - [List requests by endpoint](https://fal.ai/docs/platform-apis/v1/models/requests/by-endpoint.md): Lists requests for a specific endpoint. - [Delete request payloads](https://fal.ai/docs/platform-apis/v1/models/requests/payloads.md): Deletes the IO payloads and associated CDN output files for a specific request. - [Usage](https://fal.ai/docs/platform-apis/v1/models/usage.md): Returns paginated usage records for your workspace with filters for endpoint, user, date range, and auth method. Each item includes the billed unit quantity and unit price used to compute cost. - [Analytics](https://fal.ai/docs/platform-apis/v1/serverless/analytics.md): Time-bucketed metrics for your serverless app endpoints, including request counts, success/error rates, and latency percentiles across all inbound traffic. `prepare_duration` reflects queue/prepare time before execution; `duration` is request execution time. - [Flush Application Queue](https://fal.ai/docs/platform-apis/v1/serverless/apps/flush-queue.md): Flushes all pending requests from an application's queue. - [Queue Size](https://fal.ai/docs/platform-apis/v1/serverless/apps/queue.md): Retrieves the current queue size for a specific application. - [Download file](https://fal.ai/docs/platform-apis/v1/serverless/files/file/download.md): Downloads a file by its path. Proxies the underlying storage response. - [Upload file from URL](https://fal.ai/docs/platform-apis/v1/serverless/files/file/upload-from-url.md): Creates a new file at the target path by downloading it from the provided URL. - [Upload local file (multipart/form-data)](https://fal.ai/docs/platform-apis/v1/serverless/files/file/upload-local.md): Uploads a local file using multipart/form-data. The file field name must be `file_upload`. - [List files (root)](https://fal.ai/docs/platform-apis/v1/serverless/files/list.md): Lists files and folders in the root of your project storage. - [List files (directory)](https://fal.ai/docs/platform-apis/v1/serverless/files/list/directory.md): Lists files and folders within the specified directory path. - [Logs history (paginated)](https://fal.ai/docs/platform-apis/v1/serverless/logs/history.md): Returns paginated historical logs that match the provided filters. - [Logs stream (SSE)](https://fal.ai/docs/platform-apis/v1/serverless/logs/stream.md): Streams live logs that match the provided filters using Server-Sent Events. - [Metrics](https://fal.ai/docs/platform-apis/v1/serverless/metrics.md): Returns Prometheus-compatible metrics in text format for integration into your observability stack - [List requests by endpoint](https://fal.ai/docs/platform-apis/v1/serverless/requests/by-endpoint.md): Lists requests for endpoints owned by the authenticated user. - [List user workflows](https://fal.ai/docs/platform-apis/v1/workflows.md): List workflows for the authenticated user with optional search and filtering. - [Get workflow details](https://fal.ai/docs/platform-apis/v1/workflows/get.md): Get detailed information about a specific workflow, including its full contents/definition. ## OpenAPI Specs - [v1](https://fal.ai/docs/api-reference/platform-apis/openapi/v1.json) - [openapi](https://fal.ai/docs/api-reference/openapi.json) ## Optional - [Status](https://status.fal.ai/) - [Community](https://discord.gg/fal-ai) - [Blog](https://blog.fal.ai/)