bfl/flux-general
Flux General by BFL - generate stunning images from text prompts with state-of-the-art AI. Supports multiple aspect ratios, styles, and high-resolution output for creative and commercial use.
Input
The prompt to generate an image from.
The aspect ratio of the generated image. Allowed values: 21:9, 16:9, 3:2, 4:3, 5:4, 1:1, 4:5, 3:4, 2:3, 9:16.
020
The CFG (Classifier Free Guidance) scale is a measure of how close you want
the model to stick to your prompt when looking for a related image to show you. Range: 0 to 20.
150
The number of inference steps to perform. Range: 1 to 50.
The format of the generated image. Allowed values: jpeg, png.
The same seed and the same prompt given to the same version of the model
will output the same image every time.
The scale for NAG. Higher values will result in a image that is more distant
to the negative prompt. Maximum: 10.
05
The CFG (Classifier Free Guidance) scale is a measure of how close you want
the model to stick to your prompt when looking for a related image to show you. Range: 0 to 5.
-33
Strength of reference_only generation. Only used if a reference image is provided. Range: -3 to 3.
The LoRAs to use for the image generation which use a control image. You can use any number of LoRAs
and they will be merged together to generate the final image.
EasyControl Inputs to use for image generation.
The tau for NAG. Controls the normalization of the hidden state.
Higher values will result in a less aggressive normalization,
but may also lead to unexpected changes with respect to the original image.
Not recommended to change this value.
0.015
Base shift for the scheduled timesteps Range: 0.01 to 5.
The LoRAs to use for the image generation. You can use any number of LoRAs
and they will be merged together to generate the final image.
01
The percentage of the total timesteps when the reference guidance is to be ended. Range: 0 to 1.
The proportion of steps to apply NAG. After the specified proportion
of steps has been iterated, the remaining steps will use original
attention processors in FLUX. Maximum: 1.
01
The percentage of the total timesteps when the reference guidance is to bestarted. Range: 0 to 1.
The controlnets to use for the image generation. Only one controlnet is supported at the moment.
Uses CFG-zero init sampling as in https://arxiv.org/abs/2503.18886.
Uses classical CFG as in SD1.5, SDXL, etc. Increases generation times and price when set to be true.
If using XLabs IP-Adapter v1, this will be turned on!.
IP-Adapter to use for image generation.
Scheduler for the denoising process. Allowed values: euler, dpmpp_2m.
The controlnet unions to use for the image generation. Only one controlnet is supported at the moment.
PNG, JPEG, WebP, or GIF · 20 MiB maximum
URL of Image for Reference-Only
Sigmas schedule for the denoising process.
The alpha value for NAG. This value is used as a final weighting
factor for steering the normalized guidance (positive and negative prompts)
in the direction of the positive prompt. Higher values will result in less
steering on the normalized guidance where lower values will result in
considering the positive prompt guidance more. Maximum: 1.
0.015
Max shift for the scheduled timesteps Range: 0.01 to 5.
Use an image input to influence the generation. Can be used to fill images in masked areas.
Specifies whether beta sigmas ought to be used.
Idle
Example output — click Run to generate your own
Production endpoint
Send your first request
OpenAI-compatible endpoint with unified authentication and usage tracking.
POST
https://api.sandbase.ai/v1/runModel ID
bfl/flux-general01
Input Schema
29 parameters · 1 required · 28 optional
| Parameter | Type | Required | Description |
|---|---|---|---|
prompt | string | Required | The prompt to generate an image from. |
seed | integer | Optional | The same seed and the same prompt given to the same version of the model will output the same image every time. |
loras | object[] | Optional | The LoRAs to use for the image generation. You can use any number of LoRAs and they will be merged together to generate the final image. · Default: [] |
nag_end | number | Optional | The proportion of steps to apply NAG. After the specified proportion of steps has been iterated, the remaining steps will use original attention processors in FLUX. · Max: 1 · Default: 0.25 |
nag_tau | number | Optional | The tau for NAG. Controls the normalization of the hidden state. Higher values will result in a less aggressive normalization, but may also lead to unexpected changes with respect to the original image. Not recommended to change this value. · Default: 2.5 |
max_shift | number | Optional | Max shift for the scheduled timesteps · Min: 0.01 · Max: 5 · Default: 1.15 |
nag_alpha | number | Optional | The alpha value for NAG. This value is used as a final weighting factor for steering the normalized guidance (positive and negative prompts) in the direction of the positive prompt. Higher values will result in less steering on the normalized guidance where lower values will result in considering the positive prompt guidance more. · Max: 1 · Default: 0.25 |
nag_scale | number | Optional | The scale for NAG. Higher values will result in a image that is more distant to the negative prompt. · Max: 10 · Default: 3 |
scheduler | string | Optional | Scheduler for the denoising process. · Options: euler, dpmpp_2m · Default: "euler" eulerdpmpp_2m |
base_shift | number | Optional | Base shift for the scheduled timesteps · Min: 0.01 · Max: 5 · Default: 0.5 |
fill_image | string | Optional | Use an image input to influence the generation. Can be used to fill images in masked areas. |
controlnets | object[] | Optional | The controlnets to use for the image generation. Only one controlnet is supported at the moment. · Default: [] |
ip_adapters | object[] | Optional | IP-Adapter to use for image generation. · Default: [] |
aspect_ratio | string | Optional | The aspect ratio of the generated image. · Options: 21:9, 16:9, 3:2, 4:3, 5:4, 1:1, 4:5, 3:4, 2:3, 9:16 · Default: "16:9" 21:916:93:24:35:41:14:53:42:39:16 |
easycontrols | object[] | Optional | EasyControl Inputs to use for image generation. · Default: [] |
use_cfg_zero | boolean | Optional | Uses CFG-zero init sampling as in https://arxiv.org/abs/2503.18886. · Default: false |
use_real_cfg | boolean | Optional | Uses classical CFG as in SD1.5, SDXL, etc. Increases generation times and price when set to be true. If using XLabs IP-Adapter v1, this will be turned on!. · Default: false |
control_loras | object[] | Optional | The LoRAs to use for the image generation which use a control image. You can use any number of LoRAs and they will be merged together to generate the final image. · Default: [] |
output_format | string | Optional | The format of the generated image. · Options: jpeg, png · Default: "png" jpegpng |
reference_end | number | Optional | The percentage of the total timesteps when the reference guidance is to be ended. · Min: 0 · Max: 1 · Default: 1 |
guidance_scale | number | Optional | The CFG (Classifier Free Guidance) scale is a measure of how close you want the model to stick to your prompt when looking for a related image to show you. · Min: 0 · Max: 20 · Default: 3.5 |
real_cfg_scale | number | Optional | The CFG (Classifier Free Guidance) scale is a measure of how close you want the model to stick to your prompt when looking for a related image to show you. · Min: 0 · Max: 5 · Default: 3.5 |
sigma_schedule | string | Optional | Sigmas schedule for the denoising process. |
reference_start | number | Optional | The percentage of the total timesteps when the reference guidance is to bestarted. · Min: 0 · Max: 1 · Default: 0 |
controlnet_unions | object[] | Optional | The controlnet unions to use for the image generation. Only one controlnet is supported at the moment. · Default: [] |
use_beta_schedule | boolean | Optional | Specifies whether beta sigmas ought to be used. · Default: false |
reference_strength | number | Optional | Strength of reference_only generation. Only used if a reference image is provided. · Min: -3 · Max: 3 · Default: 0.65 |
num_inference_steps | integer | Optional | The number of inference steps to perform. · Min: 1 · Max: 50 · Default: 28 |
reference_image_url | string | Optional | URL of Image for Reference-Only |
02
Output Schema
| Field | Type | Description |
|---|---|---|
id | string | Unique identifier for the generation task |
status | string | Task status: pending, running, completed, failed, timeout |
model | string | Model used for the generation |
outputs | array | Array of output items |
outputs[].url | string | URL of the generated artifact |
outputs[].content_type | string | MIME type (e.g. image/png, video/mp4) |
error | object | null | Error details if failed, null on success |
error.type | string | Machine-readable error type code |
error.message | string | Human-readable error description |
Async Workflow
This model uses asynchronous execution. Submit a request and poll for the result.
- Submit — POST to /v1/run, receive an
id - Poll — GET /v1/run/{id} until status is
completed,failed, ortimeout - Retrieve — Read
outputsfrom the completed response
03
Code Examples
Ready-to-run snippets
# Step 1: Submit
curl -X POST https://api.sandbase.ai/v1/run \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_API_KEY" \
-d '{
"model": "bfl/flux-general",
"loras": [],
"prompt": "Extreme close-up of a single tiger eye, direct frontal view. Detailed iris and pupil. Sharp focus on eye texture and color. Natural lighting to capture authentic eye shine and depth. The word \"FLUX\" is painted over it in big, white brush strokes with visible texture.",
"nag_end": 0.25,
"nag_tau": 2.5,
"max_shift": 1.15,
"nag_alpha": 0.25,
"nag_scale": 3,
"scheduler": "euler",
"base_shift": 0.5,
"controlnets": [],
"ip_adapters": [],
"aspect_ratio": "16:9",
"easycontrols": [],
"use_cfg_zero": false,
"use_real_cfg": false,
"control_loras": [],
"output_format": "png",
"reference_end": 1,
"guidance_scale": 3.5,
"real_cfg_scale": 3.5,
"reference_start": 0,
"controlnet_unions": [],
"use_beta_schedule": false,
"reference_strength": 0.65,
"num_inference_steps": 28
}'
# Step 2: Poll result (replace <id>)
curl https://api.sandbase.ai/v1/run/<id> \
-H "Authorization: Bearer YOUR_API_KEY"API README
Flux General
Flux General belongs at the flexible visual experimentation within one workspace stage of a visual workflow. Rather than treating the model as an isolated demonstration, teams can place it inside briefing, review, selection, and handoff practices where the model serves as a broad workbench when a team expects to move between new creation and revision during the same project. This positioning clarifies why the model earns a place in a real creative pipeline and what kind of decision it helps people make.
A practical use of Flux General is creative tooling, internal prototypes, mixed image tasks, and exploratory pipelines that benefit from one adaptable foundation. Begin by agreeing on the creative objective and review criteria, prepare only the source material needed for that objective, and compare results against audience, brand, editorial, and production needs. Technical request choices remain documented below so the prose can stay focused on planning and creative value.
Highlights
Complex prompt understanding. Connects multiple subjects, relationships, lighting, typography, and style within one composition.
High-fidelity rendering. Resolves people, objects, materials, and environmental detail with a polished finish.
Reliable text integration. Places legible wording into posters, signs, packaging, and graphic layouts.
Broad aesthetic coverage. Handles realistic photography, illustration, design, and stylized imagery without one fixed look. The General configuration exposes broad FLUX synthesis behavior for workflows that need explicit control over the selected transformation method.
Pricing
| Configuration | Billing unit | Price |
|---|---|---|
| Base generation | Per request | $0.075 |
When to Use
| ✅ Good fit | ❌ Consider alternatives |
|---|---|
| The project needs this exact FLUX capability | The intended task belongs to a different media workflow |
| Required source and control media are available | Necessary assets or usage rights are unavailable |
| Creative direction can state change and preservation goals | Output must be deterministic at pixel or frame level |
| Supported dimensions and formats match final delivery | Placement requires unsupported specifications |
| An asynchronous generated result fits production | A live frame-synchronous response is mandatory |
Prompt Guide
Lead with the main subject and action, then specify composition, context, lighting, materials, style, typography, and atmosphere. For editing, identify each source and clearly separate the requested transformation from the subjects, regions, geometry, or identity that must remain unchanged.
{
"loras": [],
"nag_end": 0.25,
"prompt": "A cinematic, precisely composed result with a clear subject, controlled camera or viewpoint, realistic lighting, exact materials, and intentional atmosphere",
"seed": 1
}
Technical Specs
| Spec | Value |
|---|---|
| Model ID | bfl/flux-general |
| Input fields | seed (integer)<br>loras (array)<br>prompt (string)<br>nag_end (number; …–1)<br>nag_tau (number)<br>max_shift (number; 0.01–5)<br>nag_alpha (number; …–1)<br>nag_scale (number; …–10)<br>scheduler (string; euler, dpmpp_2m)<br>base_shift (number; 0.01–5)<br>fill_image (string)<br>controlnets (array)<br>ip_adapters (array)<br>aspect_ratio (string; 21:9, 16:9, 3:2, 4:3, 5:4, 1:1, 4:5, 3:4, 2:3, 9:16)<br>easycontrols (array)<br>use_cfg_zero (boolean)<br>use_real_cfg (boolean)<br>control_loras (array)<br>output_format (string; jpeg, png)<br>reference_end (number; 0–1)<br>guidance_scale (number; 0–20)<br>real_cfg_scale (number; 0–5)<br>sigma_schedule (string)<br>reference_start (number; 0–1)<br>controlnet_unions (array)<br>use_beta_schedule (boolean)<br>reference_strength (number; -3–3)<br>num_inference_steps (integer; 1–50)<br>reference_image_url (string) |
| Required input | prompt |
| Output fields | url, content_type |
| Execution | Asynchronous job |
Related Models
bfl/flux-general/differential-diffusion— Compare this concrete local family route.bfl/flux-general/image-to-image— Compare this concrete local family route.bfl/flux-general/inpainting— Compare this concrete local family route.