Free FLUX.1 schnell on Google Colab (ComfyUI)

Run Black Forest Labs' FLUX.1 schnell — the fastest FLUX model — for free on Google Colab T4 GPU via ComfyUI. No local GPU required.

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FLUX.1 schnell vs dev vs Stable Diffusion

Feature	SD 1.5	FLUX.1 dev	FLUX.1 schnell
Parameters	860M	12B	12B
Architecture	UNet	DiT	DiT
Steps needed	20–30	20–25	4–8
Time/image (T4)	~30–45 sec	~60–90 sec	~15–25 sec
Image quality	Good (fine-tuned)	Excellent	Very good
Prompt adherence	Moderate	Excellent	Very good
Text in images	Poor	Good	Good
License	Open	Non-commercial	Apache 2.0

schnell = "fast" in German. Distilled from FLUX.1 pro for 1–4 step generation. Slightly less detailed than dev but 3–4× faster with a fully open Apache 2.0 license.

Features

• FLUX.1 schnell fp8 — 12B DiT model, Apache 2.0 license, no Hugging Face token required
• 4-step generation — ~15–25 sec/image on T4 (faster than SD 1.5 + hires fix)
• ComfyUI — node-based interface with native FLUX support
• ComfyUI-Manager — install extra nodes in-browser
• Dual text encoders — T5-XXL fp8 (CPU-offloaded) + CLIP-L
• Cloudflare Tunnel — reliable public URL, replaces Gradio's unstable --share
• Pre-built workflow — guidance-free schnell workflow loads automatically

Quick Start

1. Click the Open in Colab badge above, or go to Google Colab → File → Upload notebook → select flux_schnell_colab.ipynb
2. Runtime → Change runtime type → Hardware accelerator: T4 GPU → Save
3. Runtime → Run all — ~6 minutes total
4. Click the trycloudflare.com URL that appears in Cell 3 output → ComfyUI opens!
5. Click Queue Prompt — first image generates in ~30–40 sec (CUDA compilation), then ~15–25 sec

Pre-configured Defaults

Setting	Value	Notes
Model	FLUX.1 schnell fp8	12B DiT, Apache 2.0
Sampler	euler	Recommended for FLUX
Scheduler	simple	Optimal for FLUX
Steps	4	Distilled sweet spot; 6–8 max
Guidance	None	schnell is guidance-free (CFG=0 baked in)
Resolution	1024 × 1024	Native FLUX resolution
T5-XXL	fp8, CPU-offloaded	Keeps GPU free for the UNet
VRAM mode	--lowvram	Streams model layers to GPU as needed

Why no guidance node? FLUX.1 schnell was distilled with cfg=0 baked in. Adding FluxGuidance degrades output quality — the workflow correctly uses BasicGuider directly.

schnell vs dev — which to use?

Use schnell when…	Use dev when…
Prototyping / trying many prompts quickly	Final high-quality renders
Need commercial license (Apache 2.0)	Personal / research use only
Want ~3–4× faster generation	Want absolute maximum detail
Batch generating variations	Quality over quantity

Both use the same ComfyUI setup and same model files (T5-XXL, CLIP-L, VAE). If you run both notebooks, Cell 2 detects existing files and skips re-downloading.

VRAM Breakdown (T4 — 15 GB)

Component	Size	Location
FLUX.1 schnell fp8	~12 GB	GPU (streamed via --lowvram)
T5-XXL fp8	~4.9 GB	CPU (offloaded)
CLIP-L	~246 MB	GPU
VAE (ae)	~335 MB	GPU

Resolution Guide

Use EmptySD3LatentImage in the workflow to change resolution:

Format	Width	Height
Square	1024	1024
Landscape	1360	768
Portrait	768	1360
Wide	1536	640

For maximum speed, use 768×768 (~8–12 sec/image at 4 steps).

Prompting Tips

• schnell has strong prompt adherence despite fewer steps — be specific
• No negative prompt needed
• Camera details improve realism: 85mm lens, f/2.8, Fujifilm XT3, film grain
• Text rendering works: a chalkboard sign that says "Daily Special"
• Style keywords: cinematic, moody, editorial lighting, golden hour, overcast
• For batch prototyping: set batch_size: 4 in EmptySD3LatentImage — 4 images in ~60 sec

Step Count Guide

Steps	Result
1	Very rough sketch, extremely fast
4	Recommended — good quality, ~15-25 sec
6–8	Marginal improvement, slower
10+	No improvement over 8 for schnell

API Usage

import requests, json, time
from PIL import Image
from io import BytesIO

BASE = "https://your-url.trycloudflare.com"

wf = json.load(open('/content/ComfyUI/user/default/workflows/flux_schnell_default.json'))
wf["4"]["inputs"]["text"] = "your prompt here"
wf["7"]["inputs"]["noise_seed"] = 99999
# wf["5"]["inputs"]["batch_size"] = 4  # generate 4 at once

prompt_id = requests.post(f"{BASE}/prompt", json={"prompt": wf}).json()["prompt_id"]

while True:
    history = requests.get(f"{BASE}/history/{prompt_id}").json()
    if prompt_id in history:
        break
    time.sleep(1)

for node_id, output in history[prompt_id]["outputs"].items():
    for img in output.get("images", []):
        data = requests.get(f"{BASE}/view", params={
            "filename": img["filename"], "subfolder": img["subfolder"], "type": img["type"]
        }).content
        Image.open(BytesIO(data)).save(f"schnell_{img['filename']}")
        print(f"Saved: schnell_{img['filename']}")

How It Works

Cell	What it does	Time
Cell 1	Clone ComfyUI + ComfyUI-Manager, install PyTorch cu121	~3-4 min
Cell 2	Download FLUX.1 schnell fp8, T5-XXL fp8, CLIP-L, VAE (~18 GB)	~3-4 min
Cell 3	Write guidance-free workflow, start Cloudflare tunnel, launch ComfyUI	~30 sec

All models Apache 2.0 / no token required:

• FLUX.1 schnell fp8 → Kijai/flux-fp8
• T5-XXL fp8 + CLIP-L → comfyanonymous/flux_text_encoders
• VAE → black-forest-labs/FLUX.1-schnell

Troubleshooting

Problem	Fix
Out of memory	--lowvram is already set. Reduce to 768×768 or lower batch size.
Blurry / low detail at 4 steps	Try 6–8 steps. Going above 8 won't help for schnell.
Workflow not loading	Click folder icon in ComfyUI → flux_schnell_default
Black / corrupted images	Re-run Cell 2 to re-download ae.safetensors
UNETLoader node missing	Re-run Cell 1 — ComfyUI may need updating
Tunnel URL missing	Look in Cell 3 output for trycloudflare.com
T5 memory warnings	Normal — T5 runs on CPU in fp8

Known Limitations

• Free Colab sessions last ~12 hours, then reset — save your images!
• The public URL changes every session
• schnell quality is slightly below dev at 4 steps (a deliberate speed/quality trade-off)

License

FLUX.1 schnell is released under the Apache 2.0 License — free for commercial use, modification, and redistribution.

Resources

• FLUX.1 schnell on Hugging Face
• ComfyUI GitHub
• ComfyUI-Manager
• ComfyUI FLUX Examples
• FLUX.1 dev notebook — higher quality, non-commercial
• r/StableDiffusion

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