FLUX.2 [flex]

Name: FLUX.2 [flex]
Brand: Black Forest Labs
Price: 0.06 USD
Availability: InStock

AI Image Editing Model

Black Forest Labs' precision image generation model with maximum control, reliable text rendering, and complete creative control supporting up to 4MP output

Try Model Benchmark examples

2048 x 2048

Max Resolution

Supported Modes

Text to Image Image Edit

Active

Details

Model ID

flux.2-flex

Also known as: flux-2-flex

Creator

Black Forest Labs

Family

flux.2

Max Input Images

Ready to integrate?

Access flux.2-flex via our unified API.

Create Account

Available at 2 providers

Starting from

$0.060 /image via fal.ai, Replicate

Prices shown are in USD · Some prices estimated from per-megapixel or per-token pricing

See all providers

Provider Performance

Fastest generation through fal at 15,813ms median latency with 100.0% success rate.

Aggregated from real API requests over the last 30 days.

Generation Time

fal

p95: 27,150ms

replicate

p95: 23,329ms

Success Rate

fal

100.0%

15 / 15 requests

replicate

100.0%

21 / 21 requests

Time to First Byte

replicate

14,961ms

p95: 22,707ms

fal

15,397ms

p95: 25,236ms

Provider Rankings

#	Provider	p50 Gen Time	p95 Gen Time	Success Rate	TTFB (p50)
1	fal	15,813ms	27,150ms	100.0%	15,397ms
2	replicate	16,147ms	23,329ms	100.0%	14,961ms

Data updated every 15 minutes. Based on all API requests through Lumenfall over the last 30 days.

Providers & Pricing (3)

FLUX.2 [flex] is available from 3 providers, with per-image pricing starting at $0.06 through fal.ai.

fal.ai

Text to Image

fal/flux.2-flex

Provider Model ID: fal-ai/flux-2-flex

$0.060 /megapixel

View pricing details

fal.ai

Image Edit

fal/flux.2-flex-edit

Provider Model ID: fal-ai/flux-2-flex/edit

Input

Megapixel

$0.060

Output

Megapixel

$0.060

Pricing Notes (4)

• Resolution is rounded up to the next megapixel, separately for each reference image and the generated image
• 1 megapixel = 1024x1024 pixels
• Each reference image is counted separately (minimum 1 MP each)
• Images exceeding 4 megapixels are resized to 4 megapixels

View official pricing • As of Dec 28, 2025

Replicate

Text to Image Image Edit

replicate/flux.2-flex

Provider Model ID: black-forest-labs/flux-2-flex

Input

Megapixel

$0.060

Output

Megapixel

$0.060

Pricing Notes (4)

• Resolution is rounded up to the next megapixel, separately for each reference image and the generated image
• 1 megapixel = 1024x1024 pixels
• Each reference image is counted separately (minimum 1 MP each)
• Images exceeding 4 megapixels are resized to 4 megapixels

View official pricing • As of Dec 30, 2025

flux-2-flex API OpenAI-compatible

Integrate FLUX.2 [flex] into your application via Lumenfall’s OpenAI-compatible API to programmatically generate 4MP images and perform high-resolution image editing. This unified endpoint provides seamless access to the model's text-to-image and creative modification capabilities.

Base URL

https://api.lumenfall.ai/openai/v1

Model

flux.2-flex

Code Examples

Text to Image

/v1/images/generations

curl -X POST \

  https://api.lumenfall.ai/openai/v1/images/generations \

  -H "Authorization: Bearer $LUMENFALL_API_KEY" \

  -H "Content-Type: application/json" \

  -d '{

    "model": "flux.2-flex",

    "prompt": "",

    "size": "1024x1024"

}'

# Response:

# { "created": 1234567890, "data": [{ "url": "https://...", "revised_prompt": "..." }] }

import OpenAI from 'openai';

const client = new OpenAI({

  apiKey: 'YOUR_API_KEY',

  baseURL: 'https://api.lumenfall.ai/openai/v1'

});

const response = await client.images.generate({

  model: 'flux.2-flex',

  prompt: '',

  size: '1024x1024'

});

// { created: 1234567890, data: [{ url: "https://...", revised_prompt: "..." }] }

console.log(response.data[0].url);

from openai import OpenAI

client = OpenAI(

    api_key="YOUR_API_KEY",

    base_url="https://api.lumenfall.ai/openai/v1"

response = client.images.generate(

    model="flux.2-flex",

    prompt="",

    size="1024x1024"

# { created: 1234567890, data: [{ url: "https://...", revised_prompt: "..." }] }

print(response.data[0].url)

Image Edit

/v1/images/edits

curl -X POST \

  https://api.lumenfall.ai/openai/v1/images/edits \

  -H "Authorization: Bearer $LUMENFALL_API_KEY" \

  -F "model=flux.2-flex" \

  -F "[email protected]" \

  -F "prompt=Add a starry night sky to this image" \

  -F "size=1024x1024"

# Response:

# { "created": 1234567890, "data": [{ "url": "https://...", "revised_prompt": "..." }] }

import OpenAI from 'openai';

import fs from 'fs';

const client = new OpenAI({

  apiKey: 'YOUR_API_KEY',

  baseURL: 'https://api.lumenfall.ai/openai/v1'

});

const response = await client.images.edit({

  model: 'flux.2-flex',

  image: fs.createReadStream('source.png'),

  prompt: 'Add a starry night sky to this image',

  size: '1024x1024'

});

// { created: 1234567890, data: [{ url: "https://...", revised_prompt: "..." }] }

console.log(response.data[0].url);

from openai import OpenAI

client = OpenAI(

    api_key="YOUR_API_KEY",

    base_url="https://api.lumenfall.ai/openai/v1"

response = client.images.edit(

    model="flux.2-flex",

    image=open("source.png", "rb"),

    prompt="Add a starry night sky to this image",

    size="1024x1024"

# { created: 1234567890, data: [{ url: "https://...", revised_prompt: "..." }] }

print(response.data[0].url)

Parameter Reference

Required Supported Not available

Core Parameters

Parameter	Type	Description	Modes
`prompt`	string	Required. Text prompt for image generation	T2I Edit
`seed`	integer	Random seed for reproducibility	T2I Edit

Size & Layout

Parameter	Type	Description	Modes
`size`	string	Image dimensions as WxH pixels (e.g. "1024x1024") or aspect ratio (e.g. "16:9") WxH determines both shape and scale (aspect_ratio and resolution are ignored when size is provided). W:H format is equivalent to aspect_ratio.	T2I Edit
`aspect_ratio`	string	Aspect ratio of the output image (e.g. "16:9", "1:1") Controls shape independently of scale. Use with resolution to control both. If size is also provided, size takes precedence. Any ratio is accepted and mapped to the nearest supported value.	T2I Edit
`resolution`	string	Output resolution tier (e.g. "1K", "4K") `auto` `1K` Controls scale independently of shape. Higher tiers produce larger images and cost more. If size is also provided, size takes precedence for scale. Any tier is accepted and mapped to the nearest supported value.	T2I Edit

Output	`size`		`aspect_ratio` + `resolution`
Flexible
Auto	`"auto"`	—	Model chooses optimal dimensions
Custom 1–14142px per side	`"WxH"`	—	Any pixel dimensions within model constraints

1K 9 sizes

Output	`size`		`aspect_ratio` + `resolution`
1183 × 887	`"1183x887"`	or	`"4:3"` + `"1K"`
916 × 1145	`"916x1145"`	or	`"4:5"` + `"1K"`
1145 × 916	`"1145x916"`	or	`"5:4"` + `"1K"`
1024 × 1024	`"1024x1024"`	or	`"1:1"` + `"1K"`
887 × 1182	`"887x1182"`	or	`"3:4"` + `"1K"`
836 × 1254	`"836x1254"`	or	`"2:3"` + `"1K"`
1254 × 836	`"1254x836"`	or	`"3:2"` + `"1K"`
768 × 1365	`"768x1365"`	or	`"9:16"` + `"1K"`
1365 × 768	`"1365x768"`	or	`"16:9"` + `"1K"`

How these parameters work

size

Exact pixel dimensions

"1920x1080"

aspect_ratio

Shape only, default scale

"16:9"

resolution

Scale tier, preserves shape

"1K"

Priority when combined

size › aspect_ratio + resolution › aspect_ratio › resolution

size is most specific and always wins. aspect_ratio and resolution control shape and scale independently.

How matching works

Shape matching – we pick the closest supported ratio. Ask for 7:1 on a model with 4:1 and 8:1, you get 8:1.

Scale matching – providers use different tier formats: K tiers (0.5K 1K 2K 4K) or megapixel tiers (0.25 1). If the exact tier isn't available, you get the nearest one.

Dimension clamping – if a model has pixel limits, we clamp dimensions to fit and keep the aspect ratio intact.

Media Inputs

Parameter	Type	Description	Modes
`image`	file	Required. Input image(s) to edit Supports PNG, JPEG, WebP.	T2I Edit

Output & Format

Parameter	Type	Description	Modes
`response_format`	string	How to return the image `url` `b64_json` Default: `"url"`	T2I Edit
`output_format`	string	Output image format `png` `jpeg` `gif` `webp` `avif` Gateway converts to requested format if provider doesn't support it natively.	T2I Edit
`output_compression`	integer	Compression level for lossy formats (JPEG, WebP, AVIF)	T2I Edit
`n`	integer	Number of images to generate Default: `1` Gateway generates multiple images in parallel even if provider only supports 1.	T2I Edit

Additional Parameters

Parameter	Type	Description	Modes
`cfg_scale`	number	Classifier-free guidance scale — higher values stick more closely to the prompt	T2I Edit
`enable_safety_checker` fal	boolean	Whether to enable the safety checker.	T2I Edit
`height` replicate	integer	Height of the generated image. Only used when aspect_ratio=custom. Must be a multiple of 16 (if it's not, it will be rounded to nearest multiple of 16).	T2I Edit
`num_inference_steps` fal	integer	The number of inference steps to perform.	T2I Edit
`output_quality` replicate	integer	Quality when saving the output images, from 0 to 100. 100 is best quality, 0 is lowest quality. Not relevant for .png outputs	T2I Edit
`prompt_upsampling` replicate	boolean	Automatically modify the prompt for more creative generation	T2I Edit
`safety_tolerance`	string	The safety tolerance level for the generated image. 1 being the most strict and 5 being the most permissive. `1` `2` `3` `4` `5`	T2I Edit
`steps` replicate	integer	Number of inference steps	T2I Edit
`sync_mode` fal	boolean	If `True`, the media will be returned as a data URI and the output data won't be available in the request history.	T2I Edit
`width` replicate	integer	Width of the generated image. Only used when aspect_ratio=custom. Must be a multiple of 16 (if it's not, it will be rounded to nearest multiple of 16).	T2I Edit

Parameter Normalization

How we handle parameters across different providers

Not every provider speaks the same language. When you send a parameter, we handle it in one of four ways depending on what the model supports:

Behavior	What happens	Example
`passthrough`	Sent as-is to the provider	style, quality
`renamed`	Same value, mapped to the field name the provider expects	prompt
`converted`	Transformed to the provider's native format	size
`emulated`	Works even if the provider has no concept of it	n, response_format

Parameters we don't recognize pass straight through to the upstream API, so provider-specific options still work.

Full API Reference Authentication, endpoints, and more

FLUX.2 [flex] Benchmarks

FLUX.2 [flex] holds the #4 rank in Image Editing with a 1228 Elo and maintains the #14 position for Text-to-Image generation with a 1240 Elo rating. These scores place the model among the top-tier competitors for precision creative control and consistent visual output.

Lumenfall Arena

Image Editing

1226 Elo

Lumenfall Arena

#18

Text-to-Image

1246 Elo

Image Editing Landscape

Elo vs Cost

Elo vs Speed

1 without speed data omitted.

Text-to-Image Landscape

Elo vs Cost

Elo vs Speed

8 without speed data omitted.

Competition Results

Image Editing

Photorealism

View leaderboard

Man and Car in California

13 models

Image Editing

Source

Edit instruction

“Make a photo of the man driving the car down the California coastline”

FLUX.2 [flex] edited result for Night Sky Transformation

Original image before FLUX.2 [flex] editing

Before After

#15

Night Sky Transformation

16 models

Image Editing

Edit instruction

“Change the scene to night: a deep, dark sky with subtle, glistening stars visible behind the mountain.”

Text-to-Image

Text Rendering

View leaderboard

#16

Modern Clean Menu

19 models

Text-to-Image

Prompt

“Modern minimalist restaurant menu design, white background with colorful food photos in grid, sections for appetizers/pizza/mains, bold sans-serif fonts, vibrant accents, clean professional layout for casual dining.”

#12

Apollo 11: Journey to Tranquility

19 models

Text-to-Image

Prompt

“Create a clean, modern vector infographic poster about the Apollo 11 mission. NASA-inspired palette (navy, white, muted red, light gray). Flat-vector style, crisp lines, consistent iconography, subtle gradients only. Steps (stop at landing): 1. Launch (Saturn Vicon) 2. Earth Orbit (Earth + orbit ring icon) 3. Translunar (trajectory arc icon) 4. Lunar Orbit (Moon + orbit ring icon) 5. Descent (lunar module descending icon) 6. Landing (lunar module on the surface icon) Small supporting elements (minimal text): • Crew strip: three silhouette icons with only last names: Armstrong, Aldrin, Collins. • Landing site marker: Moon pin labeled "Tranquility" only. Layout constraints: generous margins, large readable labels, clean background with subtle stars. Vector-only, print-poster look, high resolution.”

#20

Vintage Cafe Logo

21 models

Text-to-Image

Prompt

“Vintage minimalist restaurant logo for "Caffè Florian", retro cloche dome with steam and "Est. 1720" banner, classic typography, warm brown and cream tones, subtle texture on light background, vector emblem style.”

Text-to-Image

Photorealism

View leaderboard

#22

Candid Street Photography

24 models

Text-to-Image

Prompt

“A candid street photo of an elderly Japanese man repairing a red bicycle in light rain, reflections on wet pavement, shallow depth of field, 50mm lens, natural skin texture, imperfect framing, motion blur from passing cars, cinematic but realistic, no stylization.”

Text-to-Image

Product, Branding & Commercial

View leaderboard

#20

Vintage Cafe Logo

21 models

Text-to-Image

Prompt

Uncategorized

Intricate Floral Mandala

15 models

Text-to-Image

Prompt

“Perfectly symmetrical mandala made entirely of real flowers, petals, leaves, fruits, and seeds in vibrant natural colors, intricate layered patterns with radial symmetry, top-down view on a soft neutral background, hyper-detailed organic textures and subtle shadows, photorealistic, 8K masterpiece.”

Heroic Super Hero Portrait

21 models

Text-to-Image

Prompt

“Hyper-photorealistic full-body portrait of a female superhero standing triumphantly on a New York skyscraper rooftop at golden sunset, wearing a classic modest superhero costume with flowing cape, chest emblem, gloves, and boots in red and blue colors, practical design, short hair, strong determined heroic expression looking into the distance, powerful confident stance with hands on hips and cape billowing dramatically in the wind, detailed urban cityscape background, warm natural sunlight with sharp shadows and fabric highlights, ultra-sharp textures on suit, hair, and concrete, 8K masterpiece, empowering family-friendly style.”

Isometric Miniature Diorama Scenes

21 models

Text-to-Image

Prompt

“Create a clear, 45° top-down isometric miniature 3D cartoon scene of Japan's signature dish: sushi, with soft refined textures, realistic PBR materials, gentle lighting, on a small raised diorama base with minimal garnish and plate. Solid light blue background. At top-center: 'JAPAN' in large bold text, 'SUSHI' below it, small flag icon. Perfectly centered, ultra-clean, high-clarity, square format.”

#11

Geometric Composition

22 models

Text-to-Image

Prompt

“A glass cube on a wooden table. Inside the cube is a small blue sphere. On top of the cube sits a red book. A green plant is behind the cube, partially visible through the glass. Soft window light from the left.”

#13

Victorian Greenhouse Oasis

17 models

Text-to-Image

Prompt

“Hyper-photorealistic interior of a lush Victorian glass greenhouse filled with exotic tropical plants, vibrant blooming orchids, tall ferns, colorful butterflies in flight, sunlight filtering through ornate glass roof creating realistic caustics and dew on leaves, intricate iron framework visible, misty atmosphere, 8K masterpiece.”

#17

Adorable Baby Animals in Sunny Meadow

25 models

Text-to-Image

Prompt

“Hyper-photorealistic scene of fluffy baby animals—a golden retriever puppy, tabby kitten, baby bunny, and red fox kit—with big expressive eyes and ultra-detailed soft fur, playfully chasing butterflies and tumbling together in a lush wildflower meadow, warm golden sunrise light with god rays and dew sparkles, joyful wholesome vibe, 8K masterpiece.”

Top Matchups

See how FLUX.2 [flex] performs head-to-head against other AI models, ranked by community votes in blind comparisons.

vs Nano Banana Pro

Challenge: Night Sky Transformation

13% W · 88% L

vs GPT Image 1.5

Challenge: Man and Car in California

100% W · 0% L

vs Nano Banana

Challenge: Heroic Super Hero Portrait

33% W · 33% L · 33% T

vs Stable Diffusion 3.5 Large

Challenge: Apollo 11: Journey to Tranquility

0% W · 100% L

vs FLUX.2 [dev] Turbo

Challenge: Intricate Floral Mandala

0% W · 50% L · 50% T

FLUX.2 [flex] is best for

See all Use Cases

The model excels in high-fidelity photorealism where it ranks #4 with a 52.5% win rate, though it shows lower performance in text rendering and commercial branding categories. Its strengths are primary concentrated in photographic output rather than graphic design or typography-heavy tasks.

#5 of 16

Photorealism

Edit · 52.0% win rate

Gallery

View all 16 images

FLUX.2 [flex] FAQ

How much does FLUX.2 [flex] cost?

FLUX.2 [flex] starts at $0.06 per image through Lumenfall. Pricing varies by provider. Lumenfall does not add any markup to provider pricing.

How do I use FLUX.2 [flex] via API?

You can use FLUX.2 [flex] through Lumenfall's OpenAI-compatible API. Send requests to the unified endpoint with model ID "flux.2-flex". Code examples are available in Python, JavaScript, and cURL.

Which providers offer FLUX.2 [flex]?

FLUX.2 [flex] is available through fal.ai and Replicate on Lumenfall. Lumenfall automatically routes requests to the best available provider.

What is the maximum resolution for FLUX.2 [flex]?

FLUX.2 [flex] supports images up to 2048x2048 resolution.

Overview

FLUX.2 [flex] is a high-resolution image generation model developed by Black Forest Labs, designed specifically for workflows requiring high precision and administrative control over visual output. It supports generation up to 4 megapixels (4MP), significantly exceeding the standard 1MP outputs of many contemporary latent diffusion models. The model is built to bridge the gap between creative prompt engineering and technical asset production by prioritizing structural reliability and legible typography.

Strengths

High-Resolution Native Output: Supports images up to 4MP, allowing for greater detail in large-format prints, digital signage, and high-fidelity textures without immediate need for secondary upscaling.
Reliable Text Rendering: Demonstrates high accuracy in rendering complex strings, signage, and user-defined typography within generated scenes, a traditional failure point for many diffusion architectures.
Compositional Precision: Offers granular control over spatial arrangements and object placement, making it suitable for professional design layouts where specific element positioning is required.
Multi-Modal Flexibility: Operates effectively across text-to-image and image-to-image pipelines, maintaining stylistic consistency during iterative editing or refinement tasks.

Limitations

Computational Intensity: The increased pixel density and precision requirements result in a higher resource cost, reflected in its starting price of $0.06 per generation, making it less efficient for rapid, low-fidelity prototyping.
Latency Tradeoffs: Due to the complexity of generating 4MP outputs and the underlying FLUX.2 architecture, inference times are generally longer compared to “schnell” or distilled variants focused on speed.

Technical Background

FLUX.2 [flex] belongs to the FLUX.2 family of models, characterized by an evolved transformer-based diffusion architecture. It utilizes a flow-tracking approach to image synthesis, which improves the model’s ability to follow complex prompts and maintain global coherence at high resolutions. Black Forest Labs optimized this specific variant to maximize the signal-to-noise ratio in high-frequency details, allowing for the 4MP ceiling while maintaining anatomical and structural accuracy.

Best For

FLUX.2 [flex] is ideal for professional graphic design, advertising campaigns requiring specific font integration, and high-resolution digital art where detail and control are paramount. Developers can leverage this model to build applications for automated marketing collateral or high-fidelity asset generation where “hallucinated” text or blurry background details would be unacceptable.

You can experiment with FLUX.2 [flex] parameters and integrate it into your production environments via the Lumenfall unified API and interactive playground.

Try FLUX.2 [flex] in Playground

Generate images with custom prompts — no API key needed.

Open Playground