Flux 2 Dev Text To Image API Documentation
Playground
Try it on WaveSpeedAI!FLUX.2 [dev] from Black Forest Labs delivers fast, studio-quality text-to-image generation with enhanced realism, crisper text rendering, and native editing for rapid iteration. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.
Features
FLUX.2 [dev] is the lean base model of the FLUX.2 family: an open-source text-to-image engine tuned for speed, stability, and training friendliness. It delivers solid visual quality while staying small enough for rapid iteration, LoRA experiments, and large-scale batch jobs.
Built for
- Rapid prototyping and prompt exploration
- High-volume generation under tight cost constraints
- Research and custom training workflows (LoRA, adapters, etc.)
- Teams that need a dependable “default” model in their stack
What This Means for You
• Strong speed–quality ratio
Produces coherent, sharp images much faster than heavyweight models, keeping experimentation loops short and interactive.
• Transparent, open foundation
Built on open FLUX.2 tooling and community work, so you can inspect behaviour, plug it into your own code, and extend it without a black box.
• Resource-light generation
The compact dev configuration keeps GPU memory and runtime requirements modest, which is perfect for large batches, schedulers, and internal tools.
• Pipeline-friendly outputs
Generates standard JPEG or PNG images that slot directly into design workflows, web delivery, or later editing stages.
• Stable, repeatable behaviour
Seed control and predictable sampling make it easy to reproduce results or generate controlled variations for A/B testing, prompt tuning, and dataset creation.
Pricing
Simple per-image billing:
- $0.012 per generated image
FLUX.2 family on WaveSpeedAI
Combine FLUX.2 [dev] with the rest of the FLUX.2 lineup for a complete creation and editing workflow:
-
FLUX.2 [dev] Edit – edit and refine existing images while staying in the same lightweight, fine-tuning-friendly family:
-
FLUX.2 Flex Text-to-Image – more flexible, style-rich generation for creative exploration:
-
FLUX.2 Flex Edit – powerful image editing with broader stylistic range:
-
FLUX.2 Pro Text-to-Image – higher-capacity model for maximum quality hero shots and demanding production use:
-
FLUX.2 Pro Edit - remium editing for detailed, high-fidelity transformations:
More Image Tools on WaveSpeedAI
- Nano Banana Pro – Google’s Gemini-based text-to-image model for sharp, coherent, prompt-faithful visuals that work great for ads, keyframes, and product shots.
- Seedream V4 – ’s style-consistent, multi-image generator ideal for posters, campaigns, and large batches of on-brand illustrations.
- Qwen Edit Plus – an enhanced Qwen-based image editor for precise inpainting, cleanup, and local style changes while preserving overall composition.
Authentication
For authentication details, please refer to the Authentication Guide.
API Endpoints
Submit Task & Query Result
set -euo pipefail
export WAVESPEED_API_KEY="your-api-key"
REQUEST_BODY=$(cat <<'JSON'
{
"prompt": "A cinematic ocean wave at sunrise, highly detailed",
"size": "1024*1024"
}
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-2-dev/text-to-image" \
-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. | |
| size | string | No | 1024*1024 | 256 ~ 2048 | The size of the generated media in pixels (width*height). |
| seed | integer | No | - | - | The random seed to use for the generation. -1 means a random seed will be used. |
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 |