Flux Kontext Dev Multi Ultra Fast API Documentation
Playground
Try it on WaveSpeedAI!Experimental FLUX.1 Kontext [dev] - Multi-Ultra-Fast endpoint with native multi-image handling for batch and multi-view inputs. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Features
FLUX.1 Kontext Dev Multi Ultra Fast is a low-latency, multi-image editing model designed for fast, instruction-based image editing with richer context. Provide up to 4 reference images plus a text instruction, and the model performs controlled edits while using the references to improve consistency across identity, style, and scene—optimized for rapid iteration and production workflows.
Key capabilities
- Ultra-fast multi-image contextual editing with up to 4 reference images
- Stronger consistency by grounding edits in multiple references (identity, outfit, style, lighting, background)
- Supports both local edits and global transformations
- Ideal for iterative workflows: quick refinements with minimal drift
Typical use cases
- Multi-reference character consistency for portraits and creatives
- Product/branding edits using multiple references (logo + label + lighting + packaging)
- Background swaps with better subject matching (lighting, shadows, perspective)
- Text edits that must follow reference typography and layout
- Rapid A/B iteration for marketing assets and creative variations
Pricing
$0.025 per generation.
If you generate multiple outputs in one run, total cost = num_images × $0.025 Example: num_images = 4 → $0.10
Inputs and outputs
Input:
- Up to 4 reference images (upload or public URLs)
- One edit instruction (prompt)
Output:
- One or more edited images (controlled by num_images)
Parameters
- prompt: Edit instruction describing what to change and what to preserve
- images: Up to 4 reference images
- width / height: Output resolution
- num_inference_steps: More steps can improve fidelity but increases latency
- guidance_scale: Higher values follow the prompt more strongly; too high may over-edit
- num_images: Number of variations generated per run
- seed: Fixed value for reproducibility; -1 for random
- output_format: jpeg or png
- enable_base64_output: Return BASE64 instead of a URL (API only)
- enable_sync_mode: Wait for generation and return results directly (API only)
Prompting guide
Assign clear roles to references to avoid conflicts:
Template: Use reference 1 for [identity]. Use reference 2 for [outfit/material]. Use reference 3 for [style/lighting]. Use reference 4 for [background/scene]. Keep [must-preserve]. Change [edit request]. Match [lighting/shadows/perspective].
Example prompts
- Use reference 1 for face identity and reference 2 for hairstyle. Keep the pose from the base image. Replace the background with a clean studio setup and match shadow direction.
- Use reference 1 for the product shape and reference 2 for the label design. Replace the label text with “WaveSpeedAI”, keeping font style, perspective, and print texture consistent.
- Use reference 3 as the style guide (soft illustration look) and reference 4 for lighting mood (sunset). Preserve identity from reference 1 and keep composition unchanged.
Best practices
- Use high-quality references with clear subjects and minimal occlusion.
- Give each reference a purpose (identity vs. style vs. scene) for more reliable results.
- Iterate with one change per run for tighter control.
- Fix seed for stable comparisons across prompt variants.
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",
"num_inference_steps": 28,
"guidance_scale": 2.5,
"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-kontext-dev/multi-ultra-fast" \
-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. | |
| images | array<string> | No | - | 0 ~ 4 items | URL of images to use while generating the image. |
| size | string | No | - | 256 ~ 1536 | Advanced option. The size of the generated media in pixels (width*height). |
| num_inference_steps | integer | No | 28 | 1 ~ 50 | The number of inference steps to perform. |
| guidance_scale | number | No | 2.5 | 1 ~ 20 | The guidance scale to use for the generation. |
| 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 |