Flux Kontext Pro Multi API Documentation
Playground
Try it on WaveSpeedAI!Experimental FLUX.1 Kontext [pro] with multi-image handling to combine context from multiple images for richer output. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.
Features
FLUX Kontext Pro Multi is a fast, reliable multi-image model for context-guided generation and editing. Provide a text prompt plus up to 3 reference images, and the model uses them to improve identity consistency, style alignment, and scene coherence—ideal for practical production workflows that need strong control at a lower cost.
Key capabilities
- Multi-image contextual generation with up to 3 reference images
- Strong identity and style consistency by grounding outputs in references
- Reliable composition control for everyday creative and marketing use
- Efficient for iterative workflows and rapid A/B exploration
Typical use cases
- Character consistency using multiple portraits, outfits, or angles
- Product and branding consistency (packaging + logo + lighting references)
- Style steering with multiple exemplars (art style + texture + mood)
- Scene creation guided by reference frames
- Marketing creatives that need predictable, repeatable visual direction
Pricing
$0.04 per image.
Total cost = num_images × $0.04 Example: num_images = 4 → $0.16
Inputs and outputs
Input:
- prompt (required): Instruction describing what to generate and how to use the references
- images (required): Up to 3 reference images (upload or public URLs)
Output:
- One or more generated images (based on your num_images setting, if available in your interface)
Parameters
- prompt (required): The instruction for generation or editing
- images (required): Up to 3 reference images
- seed: Fixed value for reproducibility; leave empty/random for variation
- aspect_ratio: Output aspect ratio (e.g., 16:9, 1:1, 9:16)
Prompting guide (multi-reference)
Assign roles to references to reduce ambiguity:
Template: Use image 1 for identity. Use image 2 for outfit/material. Use image 3 for style. Generate the shot described below. Keep the key traits unchanged.
Example prompts
- Use image 1 for the person’s identity and image 2 for outfit details. Use image 3 for visual style. Create a 16:9 cinematic medium shot in a rainy city street at night. Match lighting and reflections. Keep face structure and expression consistent.
- Use image 1 for the product shape and image 2 for label layout. Use image 3 for lighting mood. Generate a clean studio product shot with realistic shadows and crisp edges. Keep branding placement consistent.
- Use images 1–2 as identity references from different angles. Create a neutral-background portrait with softbox lighting and natural skin texture. Keep proportions realistic and avoid exaggerated stylization.
Best practices
- Use high-quality references (sharp, well-lit, minimal occlusion)
- Avoid conflicting references unless you explicitly state which reference dominates (identity vs. style vs. scene)
- Let the references do most of the steering
- Fix seed when you need stable iteration and consistent comparisons
- Choose aspect_ratio intentionally to avoid awkward cropping or stretched 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",
"images": [
"https://interactive-examples.mdn.mozilla.net/media/cc0-images/painted-hand-298-332.jpg"
],
"aspect_ratio": "21:9"
}
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-pro/multi" \
-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> | Yes | - | 0 ~ 3 items | URL of images to use while generating the image. |
| seed | integer | No | - | - | The random seed to use for the generation. |
| aspect_ratio | string | No | - | 21:9, 16:9, 4:3, 3:2, 1:1, 2:3, 3:4, 9:16, 9:21 | The aspect ratio of the generated image. If not specified, it is determined automatically from the input 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 |