unsloth / text-to-image Open weights updated 1 week ago

Qwen-Image-GGUF

> [!NOTE] > This is a GGUF quantized version of Qwen-Image. > unsloth/Qwen-Image-GGUF uses Unsloth Dynamic 2.0 methodology for SOTA performance. Important layers are upcasted to higher precision.

Params
20.4 B
Context
—
Downloads 30d
136 K
Likes
36
Commercial use: allowed apache-2.0 Not gated GGUF 2 languages View on Hugging Face ↗

Download history

daily snapshots · 57 days
▲ 55 K in the last 30 days (68.9%)
136 K24 K
Sep 15Oct 4Oct 23Nov 10

Can you run it?

Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.

FileQuantSizeEst. VRAMVerdict on RTX 4090 · 24 GB
qwen-image-Q2_K.gguf Q2_K 7.7 GB 12.1 GB ✅ Runs comfortably
qwen-image-Q3_K_S.gguf Q3_K_S 8.8 GB 13.2 GB ✅ Runs comfortably
qwen-image-Q3_K_M.gguf Q3_K_M 9.0 GB 13.5 GB ✅ Runs comfortably
qwen-image-Q3_K_L.gguf Q3_K_L 10.3 GB 14.9 GB ✅ Runs comfortably
qwen-image-Q4_0.gguf Q4_0 11.9 GB 16.6 GB ✅ Runs comfortably
qwen-image-Q4_1.gguf Q4_1 12.8 GB 17.7 GB ✅ Runs comfortably
qwen-image-Q4_K_M.gguf Q4_K_M 12.8 GB 17.7 GB ✅ Runs comfortably
qwen-image-BF16.gguf GGUF 40.9 GB 48.5 GB ❌ Won’t fit
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.

Specifications

Parameters
20.4 B
Licence
apache-2.0
First seen on the Hub
2025-12-19
Base model
Qwen-Image
Training datasets
undisclosed
Added to our catalog
2026-09-15

Family

Base model and the most-downloaded derivatives in the catalog.

Compare with any text-to-image model