Qwen3.8-27B-AP-GGUF
Agention Precision quants are the highest precision quants of Qwen3.8 27B byte-for-byte. Each file has a non-uniform assignment and low-loss error correction built with a custom encoder.
Params
27.0 B
Context
—
Downloads 30d
923 K
Likes
102
Download history
daily snapshots · 10 days923 K886 K
Nov 1Nov 4Nov 7Nov 10
Can you run it?
Estimated VRAM at 8K context unless noted. Pick your hardware to see the verdict per quantization.
| File | Quant | Size | Est. VRAM | Verdict on RTX 4090 · 24 GB |
|---|---|---|---|---|
| Qwen3.8-27B-AP-IQ2_S.gguf | IQ2_S | 9.6 GB | 15.1 GB | ✅ Runs comfortably |
| Qwen3.8-27B-AP-IQ3_XXS.gguf | IQ3_XXS | 10.7 GB | 16.4 GB | ✅ Runs comfortably |
| Qwen3.8-27B-AP-IQ3_XS.gguf | IQ3_XS | 11.5 GB | 17.2 GB | ✅ Runs comfortably |
| Qwen3.8-27B-AP-IQ3_S.gguf | IQ3_S | 12.0 GB | 17.8 GB | ✅ Runs comfortably |
| Qwen3.8-27B-AP-Q3_K_XL.gguf | Q3_K_XL | 13.1 GB | 19.0 GB | ✅ Runs comfortably |
| Qwen3.8-27B-AP-IQ4_XS.gguf | IQ4_XS | 14.3 GB | 20.2 GB | ⚠️ Tight — reduce context |
| Qwen3.8-27B-AP-Q4_K_M.gguf | Q4_K_M | 16.5 GB | 22.7 GB | ⚠️ Tight — reduce context |
| Qwen3.8-27B-AP-Q4_K_XL.gguf | Q4_K_XL | 17.6 GB | 23.9 GB | ⚠️ Tight — reduce context |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Specifications
- Parameters
- 27.0 B
- Licence
- apache-2.0
- First seen on the Hub
- 2026-09-22
- Base model
- Qwen3.8-27B
- Training datasets
- undisclosed
- Added to our catalog
- 2026-11-01
Compare with any image-text-to-text model