Qwen-Image-2.1-Uncensored-Quantized vs animagine-xl-4.0
Specs, VRAM requirements and download trends — updated 10 November 2026.
cagliostrolab · B · Open weights
Params
2.6 B
Context
—
30d
1.0 M
openrail++ licence · conditional
Specification comparison
Differences are highlighted; identical values are muted.
| Specification | Qwen-Image-2.1-Uncensored-Quantized | animagine-xl-4.0 |
|---|---|---|
| Parameters | 7.1 B | 2.6 B |
| Architecture | — | — |
| Context length | — | — |
| Licence | other | openrail++ |
| Commercial use | Unknown | Conditional |
| Languages | — | 1 |
| Downloads 30d | 2,516,622 | 1,027,911 |
| Downloads all time | 4.1 M | 4.8 M |
| Quantizations on the Hub | GGUF, SAFETENSORS | SAFETENSORS |
| Gated | No | No |
| First seen on the Hub | 2026-09-20 | 2025-01-10 |
Download trend
Daily snapshots, last 29 days (13 Oct – 10 Nov)
2.8 M212 K
Qwen-Image-2.1-Uncensored-Quantized
animagine-xl-4.0
VRAM side by side
On RTX 4090 · 24 GB · 8K context unless noted
Qwen-Image-2.1-Uncensored-Quantized · Q4_0
6.1 GB / 24 GB
animagine-xl-4.0 · fp16
23.8 GB / 24 GB
Qwen-Image-2.1-Uncensored-Quantized · fp16
71.4 GB / 24 GB
Adjacent comparisons
Qwen-Image-2.1 vs Qwen-Image-2.1-Uncensored-Quantized
Krea-2 vs Qwen-Image-2.1-Uncensored-Quantized
Qwen-Image-2.1-Uncensored-GGUF vs Qwen-Image-2.1-Uncensored-Quantized
stable-diffusion-xl-base-1.0 vs animagine-xl-4.0
stable-diffusion-xl-base-1.0 vs Qwen-Image-2.1-Uncensored-Quantized
Qwen-Image-2.1-Uncensored-Quantized vs Qwen-Image-2.1-GGUF