Flux 2 Klein 9b Text To Image LoRA
Playground
Try it on WaveSpeedAI!FLUX.2 [klein] 9B with LoRA support is a high-quality text-to-image model with 9B parameters, offering enhanced realism, crisper text generation, and fast LoRA customization. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.
Features
FLUX.2 Klein 9B Text-to-Image LoRA is a powerful text-to-image generation model with full LoRA support. With 9B parameters, it delivers higher quality and detail compared to the 4B variant while maintaining fast generation. Apply custom LoRA adapters for personalized styles and characters.
Why Choose This?
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Enhanced quality 9B parameter model delivers richer detail and better prompt understanding than the 4B variant.
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LoRA support Apply custom LoRA adapters for personalized styles, characters, or visual aesthetics.
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Flexible sizing Custom width and height controls for any aspect ratio.
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Prompt Enhancer Built-in tool to automatically improve your prompts for better results.
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Balanced performance More capable than 4B while remaining fast and affordable.
Parameters
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Text description of the image you want to generate |
| width | No | Output width in pixels (default: 1024) |
| height | No | Output height in pixels (default: 1024) |
| loras | No | List of LoRA adapters to apply |
| seed | No | Random seed for reproducibility (-1 for random) |
LoRA Format
Each LoRA in the loras array has:
- path (required) — URL to the LoRA weights file
- scale (optional) — Weight multiplier, default 1
How to Use
- Write your prompt — describe the image including subject, style, lighting, and mood.
- Set size — adjust width and height for your desired dimensions.
- Add LoRAs (optional) — click ”+ Add Item” to include custom LoRA adapters.
- Set seed — use -1 for random, or specify a number for reproducibility.
- Run — submit and download the generated image.
Pricing
| Item | Cost |
|---|---|
| Per image | $0.015 |
Simple flat-rate pricing regardless of image size or LoRA count.
Best Use Cases
- Custom Character Generation — Apply character LoRAs for consistent identity.
- Style Personalization — Use style LoRAs for unique visual aesthetics.
- Brand Content — Create on-brand visuals with trained LoRA styles.
- High-Quality Output — When 4B quality isn’t enough but full-size models are overkill.
- Production Work — Balanced quality and cost for professional content.
Pro Tips
- Be specific in your prompts — include subject, style, lighting, colors, and atmosphere.
- Start with LoRA scale 1.0 and adjust based on results.
- Combine multiple LoRAs for hybrid styles (e.g., character + art style).
- Use the same seed to compare different prompts or LoRA combinations.
- If your LoRA uses trigger words, include them in your prompt.
Notes
- LoRAs can be stacked for combined effects.
- For best results, use LoRAs trained on FLUX-compatible models.
- 9B model offers better detail than 4B at slightly higher cost.
Related Models
- FLUX.2 Klein 9B Text-to-Image — Standard version without LoRA support.
- FLUX.2 Klein 4B Text-to-Image LoRA — Lighter 4B version at lower cost.
- FLUX.2 Pro — Flagship-quality text-to-image generation.
Authentication
For authentication details, please refer to the Authentication Guide.
API Endpoints
Submit Task & Query Result
set -euo pipefail
export WAVESPEED_API_KEY="your-api-key"
REQUEST_BODY=$(cat <<'JSON'
{
"prompt": "A cinematic ocean wave at sunrise, highly detailed",
"size": "1024*1024",
"seed": -1
}
JSON
)
# 1. Submit the prediction.
SUBMIT_RESPONSE=$(curl --silent --show-error --fail-with-body \
-X POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-2-klein-9b/text-to-image-lora" \
-H "Authorization: Bearer ${WAVESPEED_API_KEY}" \
-H "Content-Type: application/json" \
-d "${REQUEST_BODY}")
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 "${PREDICTION_ID}" ]; then
printf 'Submission response did not contain a prediction id
' >&2
exit 1
fi
RESULT_URL=$(printf '%s' "${TASK}" | jq -r '.urls.get // empty')
if [ -z "${RESULT_URL}" ]; then RESULT_URL="https://api.wavespeed.ai/api/v3/predictions/${PREDICTION_ID}/result"; fi
# 2. Poll until the prediction finishes.
while true; do
RESPONSE=$(curl --silent --show-error --fail-with-body \
"${RESULT_URL}" \
-H "Authorization: Bearer ${WAVESPEED_API_KEY}")
RESULT=$(printf '%s' "${RESPONSE}" | jq 'if type == "object" and has("data") then .data else . end')
STATUS=$(printf '%s' "${RESULT}" | jq -r '.status // empty')
case "${STATUS}" in
completed) printf '%s\n' "${RESULT}" | jq '.outputs'; break ;;
failed|cancelled|timeout) printf '%s\n' "${RESULT}" | jq . >&2; exit 1 ;;
created|processing) sleep 2 ;;
*) printf 'Unexpected status: %s
' "${STATUS}" >&2; exit 1 ;;
esac
doneParameters
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 | - | The size of the generated media in pixels (width*height). |
| loras | array<object> | No | 0 ~ 3 items | List of LoRAs to apply (maximum 3). | |
| seed | integer | No | -1 | - | The random seed to use for the generation. -1 means a random seed will be used. |
| enable_sync_mode | boolean | No | false | - | If set to `true`, the request attempts to wait for the generated result and return outputs in the same response. If the result is not ready within the sync wait window, the API can return a timeout body while the task continues processing. This option is only available via the API and is supported only by some models. |
| enable_base64_output | boolean | No | false | - | If set to `true`, the prediction's `output` strings are returned as **naked base64** (no `data:<mime>;base64,` prefix). When `false` (default), outputs are returned as URLs pointing to our CDN. |
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.urls.get | string | URL to retrieve the prediction result |
| data.status | string | Status of the task: created, processing, completed, or failed |
| 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.urls.get | string | URL to poll for the prediction result |
| data.status | string | Status: created, processing, completed, or failed |
| 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 |