Flux Schnell
The fastest Flux model. Generate images in under 2 seconds. Great for prototyping.
Flux Schnell is image generation AI model from Black Forest Labs, priced at β¬0.000 per 1M input tokens with a unknown context window.
Examples
See what Flux Schnell can generate
Sample output
Quick Concept
Prompt: "A friendly robot barista serving coffee in a cozy cafe, warm lighting, cartoon illustration style with soft pastel colors"
Sample output
Icon Design
Prompt: "A minimalist flat design app icon of a rocket ship launching from a phone screen, gradient purple to blue background, clean vector style"
Sample output
Food Photography
Prompt: "A rustic wooden board with assorted artisan cheeses, figs, honey drizzle, and crusty bread, overhead shot with dramatic side lighting on a dark slate surface"
Pricing
API Integration
Use our OpenAI-compatible API to integrate Flux Schnell into your application.
npm install railwailimport railwail from "railwail";
const rw = railwail("YOUR_API_KEY");
const images = await rw.run("flux-schnell", "A beautiful sunset over Tokyo");
console.log(images[0].url);
// Or use the image() method for full control
const res = await rw.image("flux-schnell", "A cat in space", {
size: "1024x1024",
n: 1,
});
console.log(res.data[0].url);Deep dive β Black Forest Labs's Flux Schnell
Black Forest Labs was founded in August 2024 in Freiburg, Germany by Robin Rombach, Patrick Esser, Andreas Blattmann and Dominik Lorenz, the original Latent Diffusion and Stable Diffusion team. After raising a $31M seed round led by Andreessen Horowitz, the lab launched the FLUX.1 family. The 'schnell' tier (German for 'fast') is positioned as the high-volume, low-latency commercial offering, available both as Apache 2.0 weights and as a commercial API endpoint on Black Forest Labs, Replicate, fal.ai and Together AI.
Visit Black Forest Labs βFLUX.1 [schnell] is the few-step distilled variant of the FLUX.1 family, optimised for sub-second inference. Architecturally it is the same 12B rectified-flow DiT as FLUX.1 [dev], using T5-XXL plus CLIP-L text encoders and a 16x latent VAE. Schnell is produced by adversarial latent-space distillation in the spirit of Adversarial Diffusion Distillation (Sauer et al. 2023), reducing the required sampling steps from 28-50 down to 1-4 with a small but measurable quality drop. The commercial schnell endpoint on Black Forest Labs and partner platforms exposes 1, 2 and 4 step modes, with 4 steps recommended for production. The model is also available open-weights under Apache 2.0 (see 'flux-1-schnell-apache'). The commercial tier additionally includes input/output safety filters and SLA support.
- Parameters
- ~12B parameters
- Context
- 512 tokens
- 1-4 step sampling β sub-second per 1MP image
- Strong photorealism and prompt adherence
- Up to 2 MP output resolution
- Decent in-image text rendering
- Available as Apache 2.0 weights for self-hosting
- Commercial API tier with SLA and safety filters
- Compatible with FLUX Tools and LoRA ecosystem
- Best for: real-time creative apps, batch generation, chat-based image generation, mobile UIs.
Same base pretraining as FLUX.1 [dev]/[pro] on a large licensed image-text corpus, followed by adversarial latent-space distillation to enable few-step sampling.
License: Dual: Apache 2.0 for the open weights (commercial use permitted); proprietary commercial license for the hosted API tier.
Known limitations
- Quality below FLUX 1.1 [pro] and Ultra
- Few-step inference reduces fidelity on complex scenes
- Hands and small text imperfect
- Open weights have no built-in safety filter
Frequently asked questions
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