Technical Specifications of flux-pro-1-1-ultra-finetuned
flux-pro-1-1-ultra-finetuned is CometAPI’s platform identifier for Black Forest Labs’ FLUX 1.1 Pro Ultra finetuned inference model, a text-to-image model designed for custom finetune-based generation. Official pricing references list FLUX1.1 [pro] Ultra at $0.06 per image and the finetuned Ultra variant at $0.07 per image, with finetuning available for FLUX 1.1 Pro family models. The model is positioned for ultra high-resolution generation, and third-party model documentation states it supports up to 4MP image output and optional raw mode for more realistic results.
Key technical points:
- Model family: FLUX 1.1 Pro Ultra finetuned inference model.
- Modality: text-to-image generation with custom finetune support via
finetune_id. - Resolution profile: supports images up to 4 megapixels.
- Special mode: supports
rawmode for a more candid, natural photographic aesthetic. - Finetune control: supports
finetune_strength, described as ranging from 0 to 2 with a default of 1 in available public documentation. - Performance note: public model documentation describes generation time of roughly 10 seconds per sample, though real performance depends on provider infrastructure and queue conditions.
What is flux-pro-1-1-ultra-finetuned?
flux-pro-1-1-ultra-finetuned is a premium image-generation model endpoint for developers who want FLUX 1.1 Pro Ultra quality combined with custom-trained concepts, styles, products, or characters. In practice, it is the finetuned version of FLUX 1.1 Pro Ultra, meaning you do not just prompt the base model—you can also apply a trained finetune_id to steer outputs toward your own visual identity or subject matter.
Compared with the standard FLUX1.1 [pro] model, the Ultra tier is positioned for higher-resolution output and premium image fidelity. The finetuned variant extends that with custom model conditioning, making it useful for brand-consistent asset creation, campaign visuals, stylized product imagery, character preservation, and reusable visual concepts across batches of generations.
Main features of flux-pro-1-1-ultra-finetuned
- Custom finetune inference: Uses a trained
finetune_id, allowing teams to generate images with their own learned style, subject, character, or product concept instead of relying only on base prompting. - Ultra-resolution output: Supports up to 4MP images, which makes it more suitable for high-detail creative workflows than standard lower-resolution text-to-image endpoints.
- Raw mode realism: Includes a
rawoption intended to reduce the polished synthetic look and produce more natural, candid, photorealistic results. - Adjustable finetune strength: Exposes
finetune_strengthso developers can tune how strongly the custom training influences the final image, balancing concept fidelity against prompt flexibility. - Production-oriented quality tier: FLUX1.1 [pro] Ultra is officially described by Black Forest Labs as an ultra high-resolution image model, and the finetuned version inherits that premium positioning for professional creative use cases.
- API-first integration path: Public ecosystem references show the model is exposed through API-based workflows and partner platforms, making it suitable for programmatic generation pipelines, internal creative tools, and automated media systems.
How to access and integrate flux-pro-1-1-ultra-finetuned
Step 1: Sign Up for API Key
To get started, create a CometAPI account and generate your API key from the dashboard. Once you have an active key, you can authenticate requests to the API and use flux-pro-1-1-ultra-finetuned as the model value in your payload.
Step 2: Send Requests to flux-pro-1-1-ultra-finetuned API
Use the standard OpenAI-compatible CometAPI endpoint and specify flux-pro-1-1-ultra-finetuned as the model ID.
curl --request POST \
--url https://api.cometapi.com/v1/responses \
--header "Authorization: Bearer $COMETAPI_API_KEY" \
--header "Content-Type: application/json" \
--data '{
"model": "flux-pro-1-1-ultra-finetuned",
"input": "A cinematic portrait of a fashion model in soft natural window light, high detail, realistic skin texture"
}'
from openai import OpenAI
client = OpenAI(
api_key="YOUR_COMETAPI_API_KEY",
base_url="https://api.cometapi.com/v1"
)
response = client.responses.create(
model="flux-pro-1-1-ultra-finetuned",
input="A cinematic portrait of a fashion model in soft natural window light, high detail, realistic skin texture"
)
print(response)
Step 3: Retrieve and Verify Results
After sending the request, parse the response object returned by CometAPI and extract the generated result according to your SDK or HTTP client. For production use, verify output quality, confirm that the returned content matches your prompt or finetune intent, and log request IDs and parameters for traceability when integrating flux-pro-1-1-ultra-finetuned into larger applications.