Inference Logoinference shell

FLUX 3 Video

FLUX 3 Video by Black Forest Labs — generate, animate, and extend video up to 20s at HD or Full HD with synchronized audio. Supports text-to-video, image-to-video with keyframes, video continuation, and draft mode.

text to videoimage to videovideo extensionnative audio
run in browser →run via APIrun with your agent
maker
bfl
category
video
input → output
text → video, image → video
runs via
api, javascript and python sdk, belt cli, mcp
updated
2026-08-04
price
From $17/sec (HD)

api reference

about

flux 3 video by black forest labs — generate, animate, and extend video up to 20s at hd or full hd with synchronized audio. supports text-to-video, image-to-video with keyframes, video continuation, and draft mode.

get an api key

create one in settings → api keys. the examples read it from INFERENCE_API_KEY.

bash
1export INFERENCE_API_KEY="inf_your_key"

1. calling the api

install the client

nothing to install. any http client works; the examples use curl, and jq to read responses. every response wraps its result in a data field.

run and get result

send "wait": true to hold the connection until the task finishes. without it the call returns right away with the task still running.

bash
12# "wait": true holds the connection until the task finishes.3# the response is {"data": {"id", "status", "status_text", "output", ...}}4curl -X POST https://api.inference.sh/apps/run \5  -H "Authorization: Bearer $INFERENCE_API_KEY" \6  -H "Content-Type: application/json" \7  -d '{8    "app": "bfl/flux-3-video",9    "input": {10      "prompt": "prompt"11    },12    "wait": true13  }'

stream live updates

get real-time progress updates as the task runs. ideal for showing progress bars, partial results, or long-running tasks. send "stream": true and the response is a server-sent event stream that ends when the task does.

bash
12# "stream": true answers with server-sent events until the task finishes3curl -N -X POST https://api.inference.sh/apps/run \4  -H "Authorization: Bearer $INFERENCE_API_KEY" \5  -H "Content-Type: application/json" \6  -d '{7    "app": "bfl/flux-3-video",8    "input": {9      "prompt": "prompt"10    },11    "stream": true12  }'

run in the background

start the task and get its id back right away, then check on it later. for long tasks, or when you'd rather be called back, see webhooks.

bash
1# without "wait" the call returns the task right away (status 1, "received")2TASK_ID=$(curl -s -X POST https://api.inference.sh/apps/run \3  -H "Authorization: Bearer $INFERENCE_API_KEY" \4  -H "Content-Type: application/json" \5  -d '{6    "app": "bfl/flux-3-video",7    "input": {8      "prompt": "prompt"9    }10  }' | jq -r '.data.id')1112# later: read its state. done when status is 10 (completed), 11 (failed) or 12 (cancelled)13curl -s https://api.inference.sh/tasks/$TASK_ID \14  -H "Authorization: Bearer $INFERENCE_API_KEY" | jq '.data | {status, status_text, 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

pass urls directly or use data uris for inline content.

bash
1# pass URLs or data URIs as input values2curl -X POST https://api.inference.sh/apps/run \3  -H "Authorization: Bearer $INFERENCE_API_KEY" \4  -H "Content-Type: application/json" \5  -d '{6    "app": "bfl/flux-3-video",7    "input": {8      "image": "https://example.com/image.png",9      "audio": "data:audio/mp3;base64,..."10    },11    "wait": true12  }'

manual upload

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

bash
1# 1. create the file: the response has an upload_url and the file's uri2FILE=$(curl -s -X POST https://api.inference.sh/files \3  -H "Authorization: Bearer $INFERENCE_API_KEY" \4  -H "Content-Type: application/json" \5  -d '{"files": [{"filename": "image.png", "content_type": "image/png"}]}')67# 2. PUT the bytes to upload_url8curl -X PUT "$(echo "$FILE" | jq -r '.data[0].upload_url')" \9  -H "Content-Type: image/png" \10  --data-binary @image.png1112# 3. pass the uri as an input value13echo "$FILE" | jq -r '.data[0].uri'

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.

bash
1curl -X POST https://api.inference.sh/apps/run \2  -H "Authorization: Bearer $INFERENCE_API_KEY" \3  -H "Content-Type: application/json" \4  -d '{5    "app": "bfl/flux-3-video",6    "input": {7        "prompt": "prompt"8    },9    "webhook": "https://your-server.com/webhook"10  }'

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 to generate.

imagestring(file)

single keyframe image. the image becomes the opening frame of the video (image-to-video).

keyframesarray

multiple keyframes as [seconds, image_url] pairs for storyboard-style generation. overrides image if both provided.

start_videostring(file)

video to continue from (video-to-video continuation).

draft_cachestring

draft cache bundle from a prior draft generation for full-quality render (draft_enhance).

resolutionstring

output resolution. hd: up to 1mp per frame. fhd: up to 2mp per frame. draft mode only supports hd.

default: "hd"
options:"hd""fhd"
durationinteger

video duration in seconds (5-20). default: auto.

min:5max:20
aspect_ratiostring

output aspect ratio.

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

generate synchronized audio. included at no extra charge.

default: true
draftboolean

generate a fast hd preview. result includes a draft_cache for later full-quality render.

default: false
safety_toleranceinteger

safety filter tolerance: 0 (strictest) to 4. default: 2.

min:0max:4

output

draft_cachestring

draft cache bundle for full-quality render. only present when draft=true.

videostring(file)*

generated video file.

other video apps

VACE

pruna/vace

$0.40/video

P-Video-Animate

pruna/p-video-animate

$0.03/sec 720p, $0.06/sec 1080p

P-Video-Upscale

pruna/p-video-upscale

Std: $0.01/sec 720p, $0.02 1080p, $0.04 2k, $0.08 4k; high fps 2x

P-Video-2-Pro-Avatar

pruna/p-video-2-pro-avatar

$0.02/sec 480p, $0.04/sec 768p, $0.06/sec 1080p, $0.08/sec 2k, $0.12/sec 4k

P-Video-2-Pro-Reference

pruna/p-video-2-pro-reference

Output: cost $0.015-$0.105/sec, speed $0.02-$0.115/sec. Ref video: $0.03-$0.06/sec. Ref img: $0.005/img. Ref audio: $0.0015-$0.0025/sec

new models

  1. Tripo Auto Rig

    tripo/tripo-rig

    3d$0.01/credit (rig check free, auto rig 25 credits, retarget 10 credits/animation)

  2. Hunyuan 3D Auto Rigging

    tencent/hunyuan-3d-auto-rigging

    3d$0.02/credit, 10 credits/call ($0.20/call)

  3. TokenRig

    infsh/tokenrig

    3dGPU time, billed per millisecond

  4. Hunyuan 3D 3.1

    tencent/hunyuan-3d-3-1

    3d$0.02/credit; Geometry 15cr, Normal 25cr, +10cr views/PBR/face-count

  5. Rodin Gen-2.5

    hyper3d/rodin-gen-2-5

    3d$0.58/credit; Extreme-High tier +0.5 credits, texture extreme-high +2 credits

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