FLUX.1 Schnell
A fast text-to-image model variant with an Apache 2.0 license, designed for rapid iteration and local ComfyUI workflows.
The brutal truth
Apache 2.0 + 8GB minimum + fast enough for real iteration is the open image sweet spot right now. FP8 quality beats most hosted alternatives at low cost.
Repository Sources & Packaging
This model is maintained across two distinct Hugging Face sources: the original creator's foundation repository and Comfy-Org's modular repack for local node pipelines.
black-forest-labs/FLUX.1-schnell
A fast text-to-image model variant with an Apache 2.0 license, designed for rapid iteration and local ComfyUI workflows.
Comfy-Org/flux1-schnell
Official Comfy-Org modular weights for FLUX.1 Schnell, with FP8 and BF16 checkpoints for ComfyUI diffusion loaders.
Files and Versions
Direct inspected tree artifacts from Hugging Face. Verified filenames, exact byte sizes, model weight shards, and configuration definitions.
Files and versions are hosted on Hugging Face. You can view all branches, commits, model weights, and tokenizer artifacts directly.
Inspect black-forest-labs/FLUX.1-schnell /tree/main ↗Inspect /tree/main Repository ↗Easy-to-Run ComfyUI Package with Official Workflow JSON
flux_schnell_bf16.safetensorsComfyUI/models/diffusion_models/text_encoder.safetensorsComfyUI/models/text_encoders/ae.safetensorsComfyUI/models/vae/- Download weights from the official Comfy-Org Hugging Face repack.
- Place each file into its corresponding
ComfyUI/models/subfolder listed in the manifest table above. - Click "⬇ Download Workflow JSON", then drag and drop the downloaded
.jsonfile into your open ComfyUI canvas.
Decision matrix
✓ RUN / USE THIS IF…
- •You have 8GB+ VRAM
- •You want Apache 2.0 for commercial work
- •You want local ComfyUI workflows
✕ WALK AWAY IF…
- •You need text rendering in images
- •You need fine-tuned styles without tooling
- •You're on CPU only
True cost of ownership
About
A fast text-to-image model variant with an Apache 2.0 license, designed for rapid iteration and local ComfyUI workflows.
What it does
Download the weights from Hugging Face, pick a quantisation that matches your GPU, and run it locally with Ollama, llama.cpp, vLLM, or a compatible runtime. Image generation runs on your own hardware — no per-token bill, no third-party data handling.
Key features
Fast generation with strong prompt adherence
Apache 2.0 removes licensing friction
Use cases
Explore visual directions before committing to production.
Place products in editorial scenes without a photo shoot.
Generate campaign imagery with consistent art direction.
Illustrate articles and decks with a consistent visual voice.
Quantization & Hardware Fit
VRAM Hardware Compatibility & Memory Allocation
| Quant | VRAM | Quality / Fit on 24GB | Install / Run Command (COMFYUI) | |
|---|---|---|---|---|
| GGUF Q4● ACTIVE | 8 GB | Standard · ✓ Fits (16GB spare) | comfy model download --url https://huggingface.co/Comfy-Org/flux1-schnell --relative-path ComfyUI/models/diffusion_models/ | |
| FP8 | 12 GB | Standard · ✓ Fits (12GB spare) | comfy model download --url https://huggingface.co/Comfy-Org/flux1-schnell --relative-path ComfyUI/models/diffusion_models/ | |
| FP16 | 24 GB | Standard · ✓ Fits (0GB spare) | comfy model download --url https://huggingface.co/Comfy-Org/flux1-schnell --relative-path ComfyUI/models/diffusion_models/ |
Buyer doubts, cleared
Can I actually run FLUX.1 Schnell on my 24GB GPU?
What's the fine print on the license?
Does the Text-to-image actually hold up in practice?
User reviews
Solid for image generation. The learning curve is real but the payoff is there. Start with the smaller build first.
Reasoning quality is close to the bigger models for structured tasks. Open-ended planning still needs a frontier model.
We evaluated FLUX.1 Schnell against two hosted alternatives. It won on cost-per-output but lost on latency. For batch work it is a clear yes.
The output reads naturally once you tune the prompt. It has cut my first-draft time roughly in half.
