FLUX 3 Max

FLUX 3 Max, post-trained FLUX 3 Video by fal and Black Forest Labs. Text-to-video, image-to-video with end frame, keyframes-to-video. 720p or 1080p, 5-20s, native audio.

run with your agent
# install belt
$curl -fsSL https://cli.inference.sh | sh
# sign in (or set INFERENCE_API_KEY on a headless machine)
$belt login
# view schema & details
$belt app get falai/flux-3-max
# run
$belt app run falai/flux-3-max --input '{"prompt":"A cinematic tracking shot through a misty forest at dawn, golden light filtering through ancient trees."}'
maker
falai
category
video
input → output
text → video, image → video
price
$0.17/sec at 720p, $0.29/sec at 1080p
runs via
api, javascript and python sdk, belt cli, mcp
updated
2026-10-20

api reference

about

flux 3 max, post-trained flux 3 video by fal and black forest labs. text-to-video, image-to-video with end frame, keyframes-to-video. 720p or 1080p, 5-20s, native audio.

1. calling the api

install the client

the client provides a convenient way to interact with the api.

bash
1pip install inferencesh

setup your api key

set INFERENCE_API_KEY as an environment variable. get your key from settings → api keys.

bash
1export INFERENCE_API_KEY="inf_your_key"

run and get result

submit a request and wait for the final result. best for batch processing or when you don't need progress updates.

python
1import os2from inferencesh import inference34client = inference(api_key=os.environ["INFERENCE_API_KEY"])567result = client.run({8        "app": "falai/flux-3-max",9        "input": {10            "prompt": "A cinematic tracking shot through a misty forest at dawn, golden light filtering through ancient trees."11        }12    })1314print(result["output"])

stream live updates

get real-time progress updates as the task runs. ideal for showing progress bars, partial results, or long-running tasks.

python
1import os2from inferencesh import inference34client = inference(api_key=os.environ["INFERENCE_API_KEY"])567# stream=True yields updates as they arrive8for update in client.run({9        "app": "falai/flux-3-max",10        "input": {11            "prompt": "A cinematic tracking shot through a misty forest at dawn, golden light filtering through ancient trees."12        }13    }, stream=True):14    if update.get("progress"):15        print(f"progress: {update['progress']}%")16    if update.get("output"):17        print(f"output: {update['output']}")

2. authentication

the api uses api keys for authentication. see the authentication docs for detailed setup instructions.

3. files

file inputs are automatically handled by the sdk. you can pass local paths, urls, or base64 data.

automatic upload

the python sdk automatically detects local file paths and uploads them. urls are passed through as-is.

python
1# local file paths are automatically uploaded2result = client.run({3    "app": "falai/flux-3-max",4    "input": {5        "image": "/path/to/local/image.png",  # detected & uploaded6        "audio": "https://example.com/audio.mp3",  # url passed through7    }8})

manual upload

you can also upload files manually and use the returned url.

python
1# upload and get a hosted URL2file = client.files.upload("/path/to/file.png")3print(file.uri)  # https://cloud.inference.sh/...

4. webhooks

get notified when a task completes by providing a webhook url. when the task reaches a terminal state (completed, failed, or cancelled), a POST request is sent to your url with the task result.

python
1result = client.run({2    "app": "falai/flux-3-max",3    "input": {4        "prompt": "A cinematic tracking shot through a misty forest at dawn, golden light filtering through ancient trees."5    },6    "webhook": "https://your-server.com/webhook"7}, wait=False)

webhook payload

your endpoint receives a JSON POST with the task result:

json
1{2  "event": "task.completed",3  "timestamp": "2024-01-15T10:30:05Z",4  "data": {5    "id": "task_abc123",6    "short_id": "abc123",7    "status": 10,8    "status_text": "completed",9    "output": { ... },10    "created_at": "2024-01-15T10:30:00Z",11    "updated_at": "2024-01-15T10:30:05Z"12  }13}
eventstringtask.completed, task.failed or task.cancelled
timestampstringiso timestamp of the delivery
data.idstringtask id
data.short_idstringshort task id
data.statusnumberterminal status (10=completed, 11=failed, 12=cancelled, 13=rejected)
data.status_textstringthe status as a word: completed, failed or cancelled
data.outputobjecttask output (when completed)
data.errorstringerror message (when failed, omitted otherwise)
data.session_idstringsession id (when the task ran in a session, omitted otherwise)
data.created_atstringiso timestamp
data.updated_atstringiso timestamp

5. schema

input

promptstring*

text prompt describing the video. for image modes, describe how the video unfolds from the image(s).

example: "A cinematic tracking shot through a misty forest at dawn, golden light filtering through ancient trees."
imagestring(file)

first frame image for image-to-video (png, jpeg, or webp).

end_imagestring(file)

optional last frame image (png, jpeg, or webp). requires image.

keyframesarray

keyframe images pinned to frame positions (max 10, unique frame_index values). cannot combine with image or end_image.

durationinteger

video duration in seconds (5-20).

default: 5min:5max:20
resolutionstring

output resolution. 720p is cheaper and faster; 1080p for best quality.

default: "720p"
options:"720p""1080p"
aspect_ratiostring

aspect ratio. auto uses 16:9 for text-to-video and follows the first image otherwise.

default: "auto"
options:"auto""21:9""2:1""16:9""4:3""1:1""3:4""9:16"
generate_audioboolean

generate a native soundtrack for the video.

default: true
reasoning_levelstring

how much effort to spend reasoning about the prompt. high is slower but follows the prompt more closely.

default: "high"
options:"low""high"
seedinteger

random seed for reproducible generation.

output

seedinteger

the seed used for generation.

videostring(file)*

the generated video file.

ready to run FLUX 3 Max?

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