RunDiffusion/Juggernaut-XL-v7-fp16-vae-fix

Juggernaut XL v7 (FP16 VAE Fix) by RunDiffusion

The fp16-safe variant of v7 — same model, fixed VAE for stable half-precision inference.

   

A drop-in replacement for Juggernaut XL v7 with the SDXL fp16 VAE fix baked in. Use this if your fp16 inference produced black images, NaN errors, or noise artifacts on the original v7. Output is otherwise identical.

When to use this variant

• 🛠️ You're running fp16 inference and the standard v7 produces black or NaN-corrupted outputs.
• 💻 You're memory-constrained and need fp16 for lower VRAM.
• 🔬 You have fp16 LoRAs or pipelines validated against this fix.

If you're running fp32/bf16 or have no fp16 issues, the standard v7 works fine.

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🚀 Skip the VAE drama. Try Juggernaut on RunDiffusion.

Every model pre-loaded with the right VAE. No installs. No precision gotchas.

Pre-loaded into ComfyUI · Forge · Automatic1111 · Fooocus · InvokeAI · SwarmUI

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The Newer Juggernauts

Model	Why upgrade
Juggernaut XL v9	Direct successor on SDXL — RunDiffusion Photo v2. 6M+ downloads.
Juggernaut X / XI	Ground-up retrains with GPT-4V captions
Juggernaut Z	Lumina-Image-2 architecture
Juggernaut Pro Flux	FLUX.1 backbone

Recommended Settings

Same as standard v7:

Parameter	Value
Resolution	832 × 1216 (portrait) · 1216 × 832 (landscape)
Sampler	DPM++ 2M Karras
Steps	30 – 40
CFG scale	3 – 7
VAE	Fp16-fixed VAE already baked in

📖 Prompting library — free to read.

Commercial Use

This model may not be deployed behind paid API services without explicit licensing. Contact juggernaut@rundiffusion.com.

Personal/creative use under CreativeML Open RAIL-M.

Credits

Juggernaut XL v7 was created by KandooAI with RunDiffusion. FP16 VAE fix applied for stable half-precision inference.

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