> ## Documentation Index > Fetch the complete documentation index at: https://fal.ai/docs/llms.txt > Use this file to discover all available pages before exploring further. # Video Generation API > Video Generation API reference. Generate videos from text prompts or images using cutting-edge video generation models. ## Overview Generate videos from text prompts or images using cutting-edge video generation models. These models support text-to-video, image-to-video, and video-to-video workflows. ## Top Models ByteDance's most advanced text-to-video model. Cinematic output with native audio, multi-shot editing, real-world physics, and director-level camera control. Example output from Seedance 2.0 Text to Video API Kling 3.0 Pro: Top-tier text-to-video with cinematic visuals, fluid motion, and native audio generation, with multi-shot support. Example output from Kling Video v3 Text to Video [Pro] 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 images. Example output from Sora 2 Veo 3.1 by Google, the most advanced AI video generation model in the world. With sound on! Example output from Veo 3.1 Generate videos from images with audio using xAI's Grok Imagine Video model. Example output from Grok Imagine Video Professional-grade video upscaling using Topaz technology. Enhance your videos with high-quality upscaling. Example output from Topaz Video Upscale Upscale your videos using SeedVR2 with temporal consistency! Example output from SeedVR2 Automatically remove backgrounds from videos -perfect for creating clean, professional content without a green screen. Example output from Video Video background removal version of bilateral reference framework (BiRefNet) for high-resolution dichotomous image segmentation (DIS) Example output from Birefnet Explore all video generation models on [fal.ai/models](https://fal.ai/models). ## Quick Start Get started with **Bytedance Seedance 2.0 Text To Video**: ```python title="Python" theme={null} import fal_client def on_queue_update(update): if isinstance(update, fal_client.InProgress): for log in update.logs: print(log["message"]) result = fal_client.subscribe( "bytedance/seedance-2.0/text-to-video", arguments={ "prompt": "An octopus finds a football in the ocean and excitedly calls its octopus friends to come and play. Cut scene to an octopus football game under the sea." }, with_logs=True, on_queue_update=on_queue_update, ) print(result) ``` ```javascript title="JavaScript" theme={null} import { fal } from "@fal-ai/client"; const result = await fal.subscribe("bytedance/seedance-2.0/text-to-video", { input: { prompt: "An octopus finds a football in the ocean and excitedly calls its octopus friends to come and play. Cut scene to an octopus football game under the sea." }, logs: true, onQueueUpdate: (update) => { if (update.status === "IN_PROGRESS") { update.logs.map((log) => log.message).forEach(console.log); } }, }); console.log(result.data); console.log(result.requestId); ``` ## Pricing For detailed pricing information, see the [fal.ai pricing page](https://fal.ai/pricing) or individual model pages.