Qwen3.8-27B-GSQ-RCO-GGUF
.json, run python tools/makeplots.py tools/results/.json then paste the printed Markdown table into "Results". The header (banner + badges) is shared across all releases. NB: the YAML block must remain the very first bytes of the file (HF requirement). -->
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tracking started — chart appears after 7 days of snapshots (6 recorded)1.2 M downloads in the last 30 days
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 |
|---|---|---|---|---|
| mmproj-Qwen3.8-27B-BF16.gguf | GGUF | 0.9 GB | 1.5 GB | ✅ Runs comfortably |
| Qwen3.8-27B-GSQ-RCO-IQ2_XS-mtp.gguf | IQ2_XS | 8.8 GB | 10.1 GB | ✅ Runs comfortably |
| Qwen3.8-27B-GSQ-RCO-IQ2_S-mtp.gguf | IQ2_S | 9.6 GB | 11.1 GB | ✅ Runs comfortably |
| Qwen3.8-27B-GSQ-RCO-IQ3_XXS-mtp.gguf | IQ3_XXS | 10.4 GB | 12.0 GB | ✅ Runs comfortably |
| Qwen3.8-27B-GSQ-RCO-IQ3_S-mtp.gguf | IQ3_S | 12.1 GB | 13.8 GB | ✅ Runs comfortably |
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.
Specifications
- Licence
- apache-2.0
- First seen on the Hub
- 2026-08-28
- Base model
- Qwen3.8-27B
- Training datasets
- undisclosed
- Added to our catalog
- 2026-09-16
Compare with any image-text-to-text model