Key features (what FLUX.2-Pro offers)

Production-oriented quality: Targeted for commercial pipelines with predictable latency and high visual fidelity (photoreal outputs up to ~4 megapixels).
Multi-reference conditioning: API support for up to 8 references via API and maintains character/style consistency across outputs — useful for brand or character continuity.
Improved typography & layout: Stronger, more legible text rendering for UI, infographics and logos compared with many prior models.
Deterministic, low-variance outputs: Pro tier optimized to reduce iterative prompting and cycle time in production.
Content provenance & safety tooling: API applies cryptographically-signed C2PA metadata to outputs; hosted endpoints include filters and inference-time moderation.
Low-latency, predictable inference ( “sub-10-second” generation speeds and SLAs for Pro).

Technical details of FLUX.2 Pro

Core architecture: FLUX.2 uses a latent flow-matching approach with a rectified-flow transformer operating in a learned latent space. The design couples that transformer backbone with a Mistral-3 24B vision-language model to provide semantic grounding and world knowledge during synthesis.
VAE and latent redesign: BFL released an updated FLUX.2 VAE (Apache-2.0) that rebalances compression, reconstruction fidelity and learnability — enabling higher-quality editing at multi-megapixel resolutions. The shared VAE underpins all FLUX.2 variants for interoperability and more consistent editing results.
Inference behavior / training techniques: The Dev checkpoint was trained with techniques such as guidance distillation to make sampling more efficient and to allow lower-step high-quality sampling; hosted Pro may use further engineering and sampling pipelines to reduce latency.

Model name: black-forest-labs/flux-2-pro

Benchmark performance

Black Forest Labs’ own evaluations and independent coverage published at launch report that FLUX.2 shows measurable gains vs several contemporary image systems in human evaluation win rates for text→image and editing tasks:

Text→image: reported win rate ~66.6% in head-to-head human comparisons vs selected models (sampled comparisons cited in the press).
Single-reference editing: ~59.8% win rate vs Qwen-Image in the reported comparisons; multi-reference editing: ~63.6% win rate . These win-rate figures were emphasized by media at launch as evidence of consistent quality and editing accuracy.

FLUX.2 vs Nano Banana Pro vs Qwen-Image

Nano Banana Pro / Google Gemini image tiers: BFL positions FLUX.2 as matching closed-source leaders on prompt fidelity and visual quality while being lower cost per image (BFL published per-MP pricing comparisons). Proprietary competitors may still claim absolute top ELOs in some curated tests but at higher per-image costs.
Hunyuan Image / Qwen-Image / other open models: FLUX.2 is reported to outperform many contemporary open checkpoints in head-to-head win-rate tests across T2I and editing tasks (per BFL’s published comparisons). Differences tend to be strongest in multi-reference consistency and typography.
FLUX.1 lineage: FLUX.2 is a full architectural redesign (not a drop-in replacement) that improves DiT blocks, autoencoder, and VLM coupling. Expect noticeable gains in editing fidelity and multi-reference coherence versus FLUX.1.

How to access Flux.2 Pro API

Log in to cometapi.com. If you are not our user yet, please register first. Sign into your CometAPI console. Get the access credential API key of the interface. Click “Add Token” at the API token in the personal center, get the token key: sk-xxxxx and submit.

Flux.2 Pro API

Step 2: Send Requests to Flux.2 Pro API

Select the “black-forest-labs/flux-2-pro ”endpoint to send the API request and set the request body. The request method and request body are obtained from our website API doc. Our website also provides Apifox test for your convenience. Replace <YOUR_API_KEY> with your actual CometAPI key from your account.

Insert your question or request into the content field—this is what the model will respond to . Process the API response to get the generated answer.

Step 3: Retrieve and Verify Results

Process the API response to get the generated answer. After processing, the API responds with the task status and output data.

CometAPI Now Supporting Replicate Format Models: 🔹 black-forest-labs/flux-2-pro 🔹 black-forest-labs/flux-2-dev 🔹 black-forest-labs/flux-2-flex

Limited Time Promotion: Lower than Replicate Official Pricing!

👇 Start Building Now Create Predictions – API Doc

⚡ Flexible Selection:

Pro: Designed for high-efficiency production and fast delivery.
Flex: Maximizes image quality with adjustable parameters.
Dev: Developer-friendly optimization.

Key features (what FLUX.2-Pro offers)

Production-oriented quality: Targeted for commercial pipelines with predictable latency and high visual fidelity (photoreal outputs up to ~4 megapixels).
Multi-reference conditioning: API support for up to 8 references via API and maintains character/style consistency across outputs — useful for brand or character continuity.
Improved typography & layout: Stronger, more legible text rendering for UI, infographics and logos compared with many prior models.
Deterministic, low-variance outputs: Pro tier optimized to reduce iterative prompting and cycle time in production.
Content provenance & safety tooling: API applies cryptographically-signed C2PA metadata to outputs; hosted endpoints include filters and inference-time moderation.
Low-latency, predictable inference ( “sub-10-second” generation speeds and SLAs for Pro).

Technical details of FLUX.2 Pro

Core architecture: FLUX.2 uses a latent flow-matching approach with a rectified-flow transformer operating in a learned latent space. The design couples that transformer backbone with a Mistral-3 24B vision-language model to provide semantic grounding and world knowledge during synthesis.
VAE and latent redesign: BFL released an updated FLUX.2 VAE (Apache-2.0) that rebalances compression, reconstruction fidelity and learnability — enabling higher-quality editing at multi-megapixel resolutions. The shared VAE underpins all FLUX.2 variants for interoperability and more consistent editing results.
Inference behavior / training techniques: The Dev checkpoint was trained with techniques such as guidance distillation to make sampling more efficient and to allow lower-step high-quality sampling; hosted Pro may use further engineering and sampling pipelines to reduce latency.

Model name: black-forest-labs/flux-2-pro

Benchmark performance

Text→image: reported win rate ~66.6% in head-to-head human comparisons vs selected models (sampled comparisons cited in the press).
Single-reference editing: ~59.8% win rate vs Qwen-Image in the reported comparisons; multi-reference editing: ~63.6% win rate . These win-rate figures were emphasized by media at launch as evidence of consistent quality and editing accuracy.

FLUX.2 vs Nano Banana Pro vs Qwen-Image

Nano Banana Pro / Google Gemini image tiers: BFL positions FLUX.2 as matching closed-source leaders on prompt fidelity and visual quality while being lower cost per image (BFL published per-MP pricing comparisons). Proprietary competitors may still claim absolute top ELOs in some curated tests but at higher per-image costs.
Hunyuan Image / Qwen-Image / other open models: FLUX.2 is reported to outperform many contemporary open checkpoints in head-to-head win-rate tests across T2I and editing tasks (per BFL’s published comparisons). Differences tend to be strongest in multi-reference consistency and typography.
FLUX.1 lineage: FLUX.2 is a full architectural redesign (not a drop-in replacement) that improves DiT blocks, autoencoder, and VLM coupling. Expect noticeable gains in editing fidelity and multi-reference coherence versus FLUX.1.

How to access Flux.2 Pro API

Flux.2 Pro API

Step 2: Send Requests to Flux.2 Pro API

Insert your question or request into the content field—this is what the model will respond to . Process the API response to get the generated answer.

Step 3: Retrieve and Verify Results

Process the API response to get the generated answer. After processing, the API responds with the task status and output data.

CometAPI Now Supporting Replicate Format Models: 🔹 black-forest-labs/flux-2-pro 🔹 black-forest-labs/flux-2-dev 🔹 black-forest-labs/flux-2-flex

Limited Time Promotion: Lower than Replicate Official Pricing!

👇 Start Building Now Create Predictions – API Doc

⚡ Flexible Selection:

Pro: Designed for high-efficiency production and fast delivery.
Flex: Maximizes image quality with adjustable parameters.
Dev: Developer-friendly optimization.

Black Forest Labs/FLUX 2 PRO

Key features (what FLUX.2-Pro offers)

Technical details of FLUX.2 Pro

Benchmark performance

FLUX.2 vs Nano Banana Pro vs Qwen-Image

How to access Flux.2 Pro API

Step 2: Send Requests to Flux.2 Pro API

Step 3: Retrieve and Verify Results

常見問題

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