Black Forest Labs: FLUX.2 Pro

black-forest-labs/flux.2-pro

Created Nov 25, 202546,864 context

$3.66/M input tokens$3.66/M output tokens

A high-end image generation and editing model focused on frontier-level visual quality and reliability. It delivers strong prompt adherence, stable lighting, sharp textures, and consistent character/style reproduction across multi-reference inputs. Designed for production workloads, it balances speed and quality while supporting text-to-image and image editing up to 4 MP resolution.

Pricing is as follows, per the docs: Input: We charge $0.015 for each megapixel on the input (i.e. reference images for editing) Output: The first megapixel is charged $0.03 and then each subsequent MP will be charged $0.015.

Providers for FLUX.2 Pro

OpenRouter routes requests to the best providers that are able to handle your prompt size and parameters, with fallbacks to maximize uptime.

Performance for FLUX.2 Pro

Compare different providers across OpenRouter

Apps using FLUX.2 Pro

Top public apps this month

Recent activity on FLUX.2 Pro

Total usage per day on OpenRouter

Prompt

515K

Completion

Reasoning

Prompt tokens measure input size. Reasoning tokens show internal thinking before a response. Completion tokens reflect total output length.

Uptime stats for FLUX.2 Pro

Uptime stats for FLUX.2 Pro across all providers

Sample code and API for FLUX.2 Pro

OpenRouter normalizes requests and responses across providers for you.

OpenRouter supports image generation through models that have image in their output modalities. These models can create images from text prompts when you specify modalities: ["image", "text"] in your request. The generated images are returned as base64-encoded data URLs in the assistant message. Learn more about image generation.

In the examples below, the OpenRouter-specific headers are optional. Setting them allows your app to appear on the OpenRouter leaderboards.

Using third-party SDKs

For information about using third-party SDKs and frameworks with OpenRouter, please see our frameworks documentation.

See the Request docs for all possible fields, and Parameters for explanations of specific sampling parameters.