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text-to-image

text-to-image

FLUX.2 Turbo Text-to-Image

wavespeed-ai/flux-2-turbo/text-to-image

FLUX 2 turbo from Black Forest Labs is the speed-optimized text-to-image model for real-time workflows. Generate photoreal images and clean typography with strong prompt adherence and consistent style—ideal for ads, posters, social posts, and rapid iteration. Built for low-latency, high-throughput use. Ready-to-use REST API, best performance, no cold starts, affordable pricing.

width
height
If set to true, the function will wait for the result to be generated and uploaded before returning the response. It allows you to get the result directly in the response. This property is only available through the API.
If enabled, the output will be encoded into a BASE64 string instead of a URL. This property is only available through the API.

Idle

Vintage 1960s American diner menu board, hand-painted wooden sign reading "BETTY'S ROADSIDE DINER" in cherry red cursive script at top, below in yellow block letters "TODAY'S SPECIAL", underneath in white chalk: "1. Classic Cheeseburger - $4.99" "2. Apple Pie à la Mode - $3.50" "3. Vanilla Milkshake - $2.75", small text at bottom reading "EST. 1962 - Open 24 Hours", coffee stain ring in corner, slightly faded paint with authentic wear, warm incandescent bulb lighting from above, chrome napkin dispenser reflection visible, photorealistic detail

Your request will cost $0.01 per run.

For $1 you can run this model approximately 100 times.

One more thing::

ExamplesView all

Vintage 1960s American diner menu board, hand-painted wooden sign reading "BETTY'S ROADSIDE DINER" in cherry red cursive script at top, below in yellow block letters "TODAY'S SPECIAL", underneath in white chalk: "1. Classic Cheeseburger - $4.99" "2. Apple Pie à la Mode - $3.50" "3. Vanilla Milkshake - $2.75", small text at bottom reading "EST. 1962 - Open 24 Hours", coffee stain ring in corner, slightly faded paint with authentic wear, warm incandescent bulb lighting from above, chrome napkin dispenser reflection visible, photorealistic detail
A busy Japanese ramen shop interior at night, exactly 7 customers sitting at the counter in a row, each person with distinctly different appearance and posture - first person slurping noodles with chopsticks raised, second person reading a manga, third person checking phone, fourth person talking to the chef, fifth person waiting with hands folded, sixth person pouring water, seventh person paying at register, elderly chef behind counter stirring a steaming pot, dense steam rising and catching warm tungsten light, wooden counter with 7 different ramen bowls at various stages of being eaten, vintage Japanese beer posters on walls, rain visible through foggy window, reflections of neon signs, Kodak Portra 800 film grain, 35mm wide angle lens distortion at edges
Extreme close-up of elderly Japanese craftsman's weathered hands performing intricate origami, fingers precisely folding red washi paper into a crane, each fold creating sharp geometric creases, visible calluses and age spots on skin, short trimmed fingernails with slight dirt underneath, wedding ring on left hand worn thin from decades, paper fibers visible at fold edges, wooden workbench surface with scattered paper scraps, natural north-facing window light, shallow depth of field with background tools blurred, macro photography level detail, every fingerprint whorl visible
Single frame containing 12 sequential phases of a hummingbird's wing beat cycle arranged in horizontal strip like Muybridge motion study, each phase showing slightly different wing position from full upstroke to full downstroke, iridescent green feathers catching light differently at each angle, frozen water droplets from nearby fountain at different positions showing trajectory, ruby red throat gorget flashing at different intensities, flower remaining static while bird moves, high-speed photography aesthetic at 10000fps equivalent, scientific motion analysis composition, each of the 12 instances razor sharp
Corporate boardroom photograph of exactly 9 executives seated around oval table, each with distinct ethnicity, age, and expression - Nigerian woman (50s) in bold red power suit leaning forward assertively, elderly Japanese man (70s) with silver hair and calm contemplative expression, young Indian man (30s) checking smartwatch impatiently, Middle Eastern woman in hijab (40s) taking notes, Scandinavian man (45) with blonde beard laughing at something off-frame, Latina woman (35) with skeptical raised eyebrow, elderly white man (75) appearing to doze off slightly, young Black man (28) in trendy glasses presenting on laptop, Chinese woman (55) with stern expression reviewing documents - glass table reflecting all faces from below, floor-to-ceiling windows showing city skyline, each person's body language telling different story, Forbes magazine corporate photography

README

FLUX.2 [turbo] — Text-to-Image

FLUX.2 [turbo] is the speed-optimized text-to-image model in the FLUX.2 family, built for ultra-fast generation with strong prompt adherence and dependable output quality. It’s ideal for real-time creation, high-volume pipelines, and rapid iteration where latency matters.

Where FLUX.2 [turbo] fits best

  • Real-time applications requiring low latency
  • High-volume batch generation workflows
  • Rapid iteration, prototyping, and creative exploration
  • Cost-sensitive production pipelines that still need consistent quality

Key benefits

  • Turbo-fast generation Optimized for minimal latency so you can generate more variations per minute.

  • Quality you can ship Designed to preserve the core FLUX.2 look and coherence while prioritizing speed.

  • Prompt-smart outputs Handles detailed prompts (objects, lighting, style cues) with reliable composition and fewer “random surprises.”

  • Format-ready files Supports common output formats including JPEG, PNG, and WebP for web, design, and production workflows.

Parameters

ParameterDescription
prompt*Text description of the desired image (the more specific the prompt, the more consistent the result).
widthOutput width (px).
heightOutput height (px).
seedUse -1 for random results, or set a fixed value for reproducible generations.

How to use

  1. Write a detailed prompt describing subject, environment, style, and lighting.

  2. Set output size by choosing width and height (square for general use, wide for banners, tall for posters).

  3. Set a seed:

    • Use -1 for random variations each run
    • Use a fixed number to reproduce a result or explore controlled variations

  4. Run the model and download the generated image.

Pricing

  • $0.01 per generated image

FLUX.2 family on WaveSpeedAI