> "The most consistent cinematic portrait results I've ever gotten from FLUX."
This is a clean, battle-tested ComfyUI workflow built around the KREA FLUX2 Dev model
(fp8_scaled) — designed from the ground up for photorealistic, cinematic portrait
generation at 1024×1024. No CFG hacks. No LoRA stacking required. Just pure FLUX power.
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⚡ WHY THIS WORKFLOW IS DIFFERENT
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✅ Uses BasicGuider — FLUX's native CFG-free guidance (no distortion, no oversaturation)
✅ SamplerCustomAdvanced pipeline — full control over noise, sigmas & sampler
✅ fp8 e4m3fn precision — runs on 8GB+ VRAM, no quality loss
✅ Dual CLIP (clip_l + t5xxl) — maximum prompt adherence
✅ Euler sampler + Simple scheduler @ 20 steps — fast, sharp, consistent
✅ Randomized seed by default — infinite variation, zero repetition
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📦 REQUIRED MODELS (place in correct folders)
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| File | Folder |
|------|--------|
| flux1-krea-dev_fp8_scaled.safetensors | /models/unet/ |
| clip_l.safetensors | /models/clip/ |
| t5xxl_fp8_e4m3fn.safetensors | /models/clip/ |
| flux2-vae.safetensors | /models/vae/ |
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🖥️ SYSTEM REQUIREMENTS
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- VRAM: 8GB minimum (12GB+ recommended for comfort)
- ComfyUI: Latest version
- Python: 3.10+
- No extra custom nodes needed — 100% native ComfyUI nodes
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✏️ STARTER PROMPT (edit the CLIPTextEncode node)
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📌 Tips for your own prompts:
- Lead with the shot type: "close-up portrait", "cinematic headshot", "golden hour photo"
- Add lighting: "soft box lighting", "rembrandt lighting", "neon backlight"
- Add lens feel: "85mm f/1.4", "shallow depth of field", "bokeh background"
- Keep it under 120 tokens — FLUX's T5 encoder handles detail natively
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⚙️ TUNING GUIDE
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| Parameter | Default | Range | Effect |
|-----------|---------|--------|--------|
| Steps | 20 | 15–30 | Higher = sharper details |
| Resolution | 1024×1024 | 768–1280 | Keep aspect ratio native |
| Scheduler | simple | simple / karras | Simple = cleaner portraits |
| Sampler | euler | euler / dpm++ | euler = most consistent |
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🔁 WORKFLOW ARCHITECTURE
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UNETLoader ──► BasicGuider ──►
DualCLIPLoader ──► CLIPTextEncode ──► BasicGuider
│
VAELoader ──────────────────────────► VAEDecode ──► SaveImage
▲
RandomNoise ──► │
KSamplerSelect ──► SamplerCustomAdvanced ──►
BasicScheduler ──►
EmptyLatentImage ──►
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❓ FAQ
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Q: Can I add a LoRA?
A: Yes! Add a LoRALoader node between UNETLoader and BasicGuider. Portrait LoRAs work great.
Q: Can I change resolution?
A: Yes, edit the EmptyLatentImage node. Keep total pixels near 1024×1024 (≈1MP).
Q: Why no negative prompt?
A: FLUX with BasicGuider is CFG-free — negative prompts don't apply. FLUX just works.
Q: My images look washed out?
A: Make sure you're using flux2-vae.safetensors. The wrong VAE kills colors.
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💬 SHARE YOUR RESULTS!
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Drop your generations in the images tab. I feature the best ones! ⭐
If this workflow saved you time, a 👍 and ⭐ mean the world.
Questions? Drop them in the comments — I reply to everything.
— socialtechie7
Description
v1.0 — Initial release
- CFG-free pipeline using BasicGuider (native FLUX guidance)
- fp8 e4m3fn precision — optimized for 8GB VRAM
- Euler sampler + Simple scheduler @ 20 steps
- Dual CLIP encoder (clip_l + t5xxl fp8) for maximum prompt adherence
- Output resolution: 1024×1024
- 100% native ComfyUI nodes — no custom nodes required





