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Generate a video from a first-frame image and prompt using Cosmos3-Super via vLLM-Omni.
The client provides a convenient way to interact with the model API.
npm install --save @fal-ai/clientThe @fal-ai/serverless-client package has been deprecated in favor of @fal-ai/client. Install the new package and update your imports — see client setup.
Set FAL_KEY as an environment variable in your runtime.
export FAL_KEY="YOUR_API_KEY"The client API handles the API submit protocol. It will handle the request status updates and return the result when the request is completed.
import { fal } from "@fal-ai/client";
const result = await fal.subscribe("nvidia/cosmos-3-super/image-to-video", {
input: {
prompt: "The camera slowly pushes in as the subject turns their head toward the light, hair drifting in a gentle breeze, dust motes floating through warm afternoon sun.",
image_url: "https://storage.googleapis.com/falserverless/example_inputs/hunyuan_i2v.jpg"
},
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);The API uses an API Key for authentication. It is recommended you set the FAL_KEY environment variable in your runtime when possible.
import { fal } from "@fal-ai/client";
fal.config({
credentials: "YOUR_FAL_KEY"
});When running code on the client-side (e.g. in a browser, mobile app or GUI applications), make sure to not expose your FAL_KEY. Instead, use a server-side proxy to make requests to the API. For more information, check out our server-side integration guide.
The client API provides a convenient way to submit requests to the model.
import { fal } from "@fal-ai/client";
const { request_id } = await fal.queue.submit("nvidia/cosmos-3-super/image-to-video", {
input: {
prompt: "The camera slowly pushes in as the subject turns their head toward the light, hair drifting in a gentle breeze, dust motes floating through warm afternoon sun.",
image_url: "https://storage.googleapis.com/falserverless/example_inputs/hunyuan_i2v.jpg"
},
webhookUrl: "https://optional.webhook.url/for/results",
});You can fetch the status of a request to check if it is completed or still in progress.
import { fal } from "@fal-ai/client";
const status = await fal.queue.status("nvidia/cosmos-3-super/image-to-video", {
requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b",
logs: true,
});Once the request is completed, you can fetch the result. See the Output Schema for the expected result format.
import { fal } from "@fal-ai/client";
const result = await fal.queue.result("nvidia/cosmos-3-super/image-to-video", {
requestId: "764cabcf-b745-4b3e-ae38-1200304cf45b"
});
console.log(result.data);
console.log(result.requestId);Some attributes in the API accept file URLs as input. Whenever that's the case you can pass your own URL or a Base64 data URI.
You can pass a Base64 data URI as a file input. The API will handle the file decoding for you. Keep in mind that for large files, this alternative although convenient can impact the request performance.
You can also pass your own URLs as long as they are publicly accessible. Be aware that some hosts might block cross-site requests, rate-limit, or consider the request as a bot.
We provide a convenient file storage that allows you to upload files and use them in your requests. You can upload files using the client API and use the returned URL in your requests.
import { fal } from "@fal-ai/client";
const file = new File(["Hello, World!"], "hello.txt", { type: "text/plain" });
const url = await fal.storage.upload(file);The client will auto-upload the file for you if you pass a binary object (e.g. File, Data).
Read more about file handling in our file upload guide.
prompt string* requiredText prompt describing the motion and scene of the video to generate.
image_url string* requiredURL of the conditioning first-frame image for the video.
negative_prompt stringContent to steer the generation away from (artifacts, unwanted motion). Defaults to NVIDIA's recommended i2v negative prompt; pass an empty string to disable. Default value: "The video captures a series of frames showing macroblocking artifacts, chromatic aberration, high-frequency noise, and rolling shutter distortion. It includes static with no motion, motion blur, over-saturation, shaky footage, low resolution, grainy texture, pixelated images, poorly lit areas, underexposed and overexposed scenes, poor color balance, washed out colors, choppy sequences, jerky movements, low frame rate, bit-depth compression artifacts, color banding, unnatural transitions, outdated special effects, fake elements, unconvincing visuals, poorly edited content, jump cuts, hard cut, visual noise, and flickering. It features moiré patterns, edge halos, and temporal aliasing. Furthermore, the content defies common sense, generating illogical scenarios, nonsensical entities, absurd character behaviors, and conceptual paradoxes that violate basic human reasoning and everyday reality. The video looks like a surreal or glitchy hallucination. Overall, the video is of poor quality."
enable_prompt_expansion booleanIf true, the Cosmos3-Nano Reasoner (a VLM that sees the first frame) rewrites the prompt into the dense caption Cosmos3 was trained on. The app starts a local Reasoner by default, or uses COSMOS_PROMPT_UPSAMPLER_BASE_URL when configured. Falls back to the raw prompt if expansion fails. Default value: true
enable_agentic_generation booleanEnable the iterative Cosmos agentic loop: prompt upsampling, candidate video generation, VLM critique of sampled frames, and prompt rewrite. Each candidate is a full render, so this is substantially slower and costlier than a single generation.
agentic_max_iterations integerMaximum agentic prompt stages when agentic generation is enabled. Default value: 2
agentic_samples_per_iteration integerCandidate videos to generate and judge per agentic iteration. The best candidate advances to the next rewrite stage. Default value: 2
agentic_early_stop booleanStop the agentic loop early when the critic score clears the strict quality threshold. Default value: true
The size of the generated video. The request is clamped and snapped to the nearest supported NVIDIA tier (256p/480p/720p) and aspect ratio.
Possible enum values: square_hd, square, portrait_4_3, portrait_16_9, landscape_4_3, landscape_16_9
Note: For custom image sizes, you can pass the width and height as an object:
"image_size": {
"width": 1280,
"height": 720
}num_frames integerNumber of frames to generate. More frames yield a longer video. Default value: 189
frames_per_second integerFrames per second of the output video. Default value: 24
num_inference_steps integerNumber of denoising steps. More steps yield higher quality but take longer. Default value: 28
guidance_scale floatClassifier-free guidance scale. Higher values increase prompt adherence at the cost of diversity. Default value: 6
seed integerThe same seed and prompt given to the same model version will produce the same video every time.
enable_safety_checker booleanEnable content moderation for the input prompt and image. Disabling it requires account authorization; unauthorized requests are always checked. Default value: true
sync_mode booleanIf True, the video is returned as a data URI and the output data won't be available in the request history.
{
"prompt": "The camera slowly pushes in as the subject turns their head toward the light, hair drifting in a gentle breeze, dust motes floating through warm afternoon sun.",
"image_url": "https://storage.googleapis.com/falserverless/example_inputs/hunyuan_i2v.jpg",
"negative_prompt": "The video captures a series of frames showing macroblocking artifacts, chromatic aberration, high-frequency noise, and rolling shutter distortion. It includes static with no motion, motion blur, over-saturation, shaky footage, low resolution, grainy texture, pixelated images, poorly lit areas, underexposed and overexposed scenes, poor color balance, washed out colors, choppy sequences, jerky movements, low frame rate, bit-depth compression artifacts, color banding, unnatural transitions, outdated special effects, fake elements, unconvincing visuals, poorly edited content, jump cuts, hard cut, visual noise, and flickering. It features moiré patterns, edge halos, and temporal aliasing. Furthermore, the content defies common sense, generating illogical scenarios, nonsensical entities, absurd character behaviors, and conceptual paradoxes that violate basic human reasoning and everyday reality. The video looks like a surreal or glitchy hallucination. Overall, the video is of poor quality.",
"enable_prompt_expansion": true,
"agentic_max_iterations": 2,
"agentic_samples_per_iteration": 2,
"agentic_early_stop": true,
"image_size": {
"height": 480,
"width": 832
},
"num_frames": 189,
"frames_per_second": 24,
"num_inference_steps": 28,
"guidance_scale": 6,
"enable_safety_checker": true
}The generated video.
seed integer* requiredThe seed used for generation.
{
"video": {
"content_type": "video/mp4",
"url": "https://v3b.fal.media/files/b/0a8fc99c/cosmos3-i2v-example.mp4"
},
"seed": 1143
}width integerThe width of the generated image. Default value: 512
height integerThe height of the generated image. Default value: 512
url string* requiredThe URL where the file can be downloaded from.
content_type stringThe mime type of the file.
file_name stringThe name of the file. It will be auto-generated if not provided.
file_size integerThe size of the file in bytes.
width integerThe width of the video
height integerThe height of the video
fps floatThe FPS of the video
duration floatThe duration of the video
num_frames integerThe number of frames in the video