Flux Schnell API Documentation
Playground
Try it on WaveSpeedAI!FLUX.1 [schnell] is a 12B rectified flow transformer for high-quality text-to-image generation via API. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Features
wavespeed-ai/flux-schnell is an ultra-fast text-to-image model designed for high-throughput generation and rapid iteration. It’s ideal when you want to explore ideas quickly, batch-generate variations, or power real-time creative workflows with consistent, production-friendly latency.
What it’s good at
- Fast text-to-image generation for rapid prompt iteration
- High-throughput batches (great for grids, A/B testing, and variations)
- Concepting & ideation (style exploration, composition discovery)
- Lightweight production use where speed matters more than maximum fidelity
Inputs
- prompt (required): your text description
- image (optional): reference image (if enabled in your deployment)
- mask_image (optional): mask for inpainting / local edits (if enabled)
- strength (optional): how strongly the model follows the reference/mask edit intent
- size: output resolution (width/height)
- num_images: number of images to generate
- seed: random seed (-1 for random)
- output_format: output format (e.g., jpeg)
- enable_base64_output (API only): return base64 instead of a URL
- enable_sync_mode (API only): wait for generation to finish before returning
Recommended settings
- Quick iterations: keep prompts short and specific, generate multiple candidates (num_images > 1)
- More control: lock the seed, then tweak one prompt element at a time
- Editing/inpainting: start with strength ~0.6–0.85, then adjust based on how much change you want
Use cases
- Marketing creative drafts: generate dozens of on-brand concept options fast
- Game & animation concept art: rapid character/prop/environment exploration
- Design exploration: packaging, posters, thumbnails, UI mood boards
- Prompt prototyping: build “prompt recipes” before switching to higher-fidelity models
- Batch generation pipelines: large-scale variation sweeps for selection and ranking
Pricing
| Model | Price per image |
|---|---|
| wavespeed-ai/flux-schnell | $0.003 |
Authentication
For authentication details, please refer to the Authentication Guide.
API Endpoints
Submit Task & Query Result
set -euo pipefail
export WAVESPEED_API_KEY="your-api-key"
REQUEST_BODY=$(cat <<'JSON'
{
"prompt": "A cinematic ocean wave at sunrise, highly detailed",
"strength": 0.8,
"size": "1024*1024",
"num_images": 1,
"output_format": "jpeg"
}
JSON
)
# 1. Submit the prediction once. Never retry this request automatically:
# a retry after an unclear failure can create a second, billed task.
CHECK='The task may already exist. Check History or the predictions list before submitting again.'
if ! SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
--connect-timeout 10 --max-time 60 \
-X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-schnell" \
-H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
-H "Content-Type: application/json" \
-d "${REQUEST_BODY}"); then
printf 'Submit failed. %s\n' "${CHECK}" >&2
exit 1
fi
TASK=$(printf '%s' "${SUBMIT_RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
PREDICTION_ID=$(printf '%s' "${TASK}" | jq -r '.id // empty')
if [ -z "${PREDICTION_ID}" ]; then
printf 'Submission response did not contain a prediction id. %s\n' "${CHECK}" >&2
exit 1
fi
RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result"
# 2. Poll until the prediction reaches a final status.
BODY_FILE=$(mktemp)
trap 'rm -f "${BODY_FILE}"' EXIT
while true; do
# Transient errors (429, 5xx) are retried, honoring Retry-After.
HTTP_CODE=$(curl --silent --show-error --fail-with-body \
--connect-timeout 10 --max-time 60 --retry 5 --retry-delay 2 \
--output "${BODY_FILE}" --write-out '%{http_code}' \
"${RESULT_URL}" \
-H "Authorization: Bearer ${WAVESPEED_API_KEY}" || true)
case "${HTTP_CODE}" in
2??) ;;
000|429|5??) # dropped connection or temporary error: keep polling
printf 'Task %s: HTTP %s, polling again in 10s\n' "${PREDICTION_ID}" "${HTTP_CODE}" >&2
sleep 10; continue ;;
*) printf 'Task %s: HTTP %s\n' "${PREDICTION_ID}" "${HTTP_CODE}" >&2
cat "${BODY_FILE}" >&2; exit 1 ;;
esac
RESULT=$(jq 'if type == "object" and has("data") then .data else . end' "${BODY_FILE}")
STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')
case "${STATUS}" in
completed) printf '%s\n' "${RESULT}" | jq '.outputs'; break ;;
failed|cancelled|timeout|deleted)
printf 'Task %s ended with status %s\n' "${PREDICTION_ID}" "${STATUS}" >&2
printf '%s\n' "${RESULT}" | jq . >&2; exit 1 ;;
*) sleep 2 ;;
esac
doneRetry temporary errors only while polling, never the submit request. Errors, retries and timeouts
Parameters
Task Submission Parameters
Request Parameters
| Parameter | Type | Required | Default | Range | Description |
|---|---|---|---|---|---|
| prompt | string | Yes | - | The positive prompt for the generation. | |
| image | string | No | - | - | |
| mask_image | string | No | - | The mask image tells the model where to generate new pixels (white) and where to preserve the original image (black). It acts as a stencil or guide for targeted image editing. | |
| strength | number | No | 0.8 | 0 ~ 1 | Strength indicates extent to transform the reference image. |
| size | string | No | 1024*1024 | 256 ~ 1536 | The size of the generated media in pixels (width*height). |
| num_images | integer | No | 1 | 1 ~ 4 | The number of images to generate. |
| seed | integer | No | - | - | The random seed to use for the generation. -1 means a random seed will be used. |
| output_format | string | No | jpeg | jpeg, png, webp | The format of the output image. |
Every model also accepts the global request options enable_sync_mode and enable_base64_output; see their pages for details.
Response Parameters
| Parameter | Type | Description |
|---|---|---|
| code | integer | HTTP status code (e.g., 200 for success) |
| message | string | Status message (e.g., “success”) |
| data.id | string | Unique identifier for the prediction, Task Id |
| data.model | string | Model ID used for the prediction |
| data.outputs | array | Output values, usually URL strings; some models return text strings or structured result objects (empty when status is not completed) |
| data.urls | object | Object containing related API endpoints |
| data.status | string | Task status. completed is successful; failed, cancelled, timeout, and deleted are failure terminal statuses. |
| data.created_at | string | ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”) |
| data.error | string | Error message (empty if no error occurred) |
| data.timings | object | Object containing timing details |
| data.timings.inference | integer | Inference time in milliseconds |
Result Request Parameters
| Parameter | Type | Required | Default | Description |
|---|---|---|---|---|
| id | string | Yes | - | Task ID |
Result Response Parameters
| Parameter | Type | Description |
|---|---|---|
| code | integer | HTTP status code (e.g., 200 for success) |
| message | string | Status message (e.g., “success”) |
| data | object | The prediction data object containing all details |
| data.id | string | Unique identifier for the prediction |
| data.model | string | Model ID used for the prediction |
| data.outputs | array<string | object> | Array of generated outputs (empty when status is not completed). Items are usually URL strings, but may be text strings or structured result objects, depending on the model. |
| data.urls | object | Object containing related API endpoints |
| data.status | string | Status: completed is successful; failed, cancelled, timeout, and deleted are failure terminal statuses |
| data.created_at | string | ISO timestamp of when the request was created |
| data.error | string | Error message (empty if no error occurred) |
| data.timings | object | Object containing timing details |
| data.timings.inference | integer | Inference time in milliseconds |