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black-forest-labs/flux-2-flex/text-to-image
FLUX.2 Flex Text-to-image
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FLUX.2 Flex Text-to-Image API by Black Forest Labs

black-forest-labs/flux-2-flex/text-to-image
Text-to-image

FLUX.2 Flex is a professional text-to-image generation model specialized for typography, fine detail preservation, and production workflows requiring precise customization. It provides adjustable inference steps (1–50) and guidance scale (1.5–10) for fine-grained control, delivering high-quality output up to 4MP.

FLUX.2 Flex — Text to Image

Developer: Black Forest Labs
Model ID: black-forest-labs/flux-2-flex/text-to-image
Release Date: February 23, 2026

Overview

FLUX.2 Flex is a professional text-to-image generation model specialized for typography, fine detail preservation, and production workflows requiring precise customization. Built on latent flow matching with a rectified flow transformer architecture, it provides adjustable inference steps (1–50) and a guidance scale (1.5–10) for fine-grained control over the diffusion process.

Compared to FLUX.2 Pro, FLUX.2 Flex offers greater parameter control — making it the preferred choice for workflows that require balancing speed against output quality, or for tasks where text rendering and hex-accurate color are critical. The latest version is up to 3× faster than previous FLUX.2 Flex releases while maintaining the same high output quality.

Key Capabilities

  • Superior typography — Reliable text rendering for complex typography, infographics, memes, UI mockups, and marketing materials with legible fine text.
  • Adjustable inference parameters — Fine-grained control through configurable steps (1–50) and guidance scale (1.5–10) to balance quality, speed, and prompt adherence.
  • High-resolution output up to 4MP — Flexible aspect ratios with a fundamentally improved VAE achieving 63.5% better learnability (gFID) and 84.1% better reconstruction quality (LPIPS) versus prior architectures.
  • HEX color accuracy — Precise color matching using hex color codes for brand-accurate asset creation.
  • Prompt expansion — Optional automatic prompt enrichment to improve output quality from short or simple prompts.

Use Cases

  • Typography and text-heavy design — Infographics, magazine spreads, UI mockups, price tags, labels, and promotional materials requiring accurate text rendering.
  • Brand asset creation — Logos, signage, and branded content with hex-code color accuracy.
  • E-commerce and product design — Product descriptions, marketing materials, and campaign imagery.
  • UI/UX design — Wireframes, interface mockups, and design systems with legible text elements.
  • Advertising and media — Static ads, intro screens, credits, and text overlays.
  • Rapid prototyping — Use lower step counts (6–20) for fast visual exploration; increase steps (40–50) for final-quality deliverables.

Input Parameters

ParameterTypeDefaultRangeDescription
promptstringText description of the image to generate. Required.
widthinteger1024256–2048Width of the generated image in pixels.
heightinteger1024256–2048Height of the generated image in pixels.
stepsinteger501–50Number of diffusion inference steps. Lower values are faster; higher values produce maximum fidelity.
guidancenumber51.5–10Guidance scale controlling how strictly the model follows the prompt. Higher values increase prompt adherence.
enable_prompt_expansionbooleantrueWhen enabled, the model automatically expands short prompts to improve output quality.
output_formatstringjpegjpeg, pngOutput image format.
safety_toleranceinteger20–5Moderation strictness level. 0 = most strict, 5 = least strict.
seedinteger-1Random seed for reproducibility. Use -1 for a random seed.

Steps vs. Quality Trade-off

Steps RangeRecommended Use
6–20Rapid prototyping, fast iteration
20–40Balanced quality for general use
40–50Maximum fidelity for final deliverables

Output

Returns a URL to the generated image. The model supports asynchronous generation: the response first contains a polling URL, which resolves to the final image once generation is complete.

Output formats: JPEG, PNG Maximum resolution: 4 megapixels (e.g., 2048×2048)

Note: FLUX.2 Flex exhibits higher latency compared to FLUX.2 Pro, reflecting its emphasis on quality and fine-grained customization over raw speed.

Pricing

Pricing is based on the resolution of the generated image, measured in megapixels (MP). 1 MP = 1,048,576 pixels (e.g., 1024×1024). Resolution is capped at 4 MP for billing purposes.

SKUs

SKUDescriptionUnit Price
sku_mpPer megapixel of the generated image (up to 4 MP)$0.05

Formula

cost = min(4, ceil(width × height / 1,048,576)) × sku_mp

Examples

ResolutionMegapixels (billed)Cost
1024×10241 MP$0.050
1024×15362 MP$0.100
1536×15363 MP (ceil)$0.150
2048×20484 MP$0.200

Megapixels are always rounded up (ceil) and capped at 4 MP. A flat per-megapixel rate applies uniformly across all resolution tiers, with no differentiated first-megapixel pricing.

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