batiai / text-generation Open weights updated 2 months ago

Qwen3.6-27B-GGUF

> 🆕 Newer model available — Qwen3.8-27B GGUF > Qwen's 2026-08 release. Same 27B class, six quants from 10 GB, vision included, Korean-verified. > ollama run batiai/qwen3.8-27b:iq4

Params
27.0 B
Context
—
Downloads 30d
150 K
Likes
8
Commercial use: allowed apache-2.0 Not gated GGUF 4 languages View on Hugging Face ↗

Download history

daily snapshots · 90 days
▲ 7 K in the last 30 days (4.6%)
159 K147 K
Jul 28Aug 27Sep 26Oct 25

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
mmproj-Qwen-Qwen3.6-27B-BF16.gguf GGUF 0.9 GB 5.6 GB ✅ Runs comfortably
Qwen-Qwen3.6-27B-IQ3_XXS.gguf IQ3_XXS 11.2 GB 16.9 GB ✅ Runs comfortably
Qwen-Qwen3.6-27B-Q3_K_M.gguf Q3_K_M 13.3 GB 19.2 GB ✅ Runs comfortably
Qwen-Qwen3.6-27B-IQ4_XS.gguf IQ4_XS 15.1 GB 21.1 GB ⚠️ Tight — reduce context
Qwen-Qwen3.6-27B-Q4_K_M.gguf Q4_K_M 16.5 GB 22.8 GB ⚠️ Tight — reduce context
Qwen-Qwen3.6-27B-Q6_K.gguf Q6_K 22.1 GB 28.8 GB ❌ Won’t fit
Estimate: file size × 1.1 + KV cache at 8K + 0.5 GB overhead. Not a benchmark — how we calculate this.

Run it

copy-paste, exact tags checked against the Hub
~ · ollama · Q4_K_M
$ ollama run qwen3-6-27b-gguf

# pin the quantization explicitly
$ ollama run qwen3-6-27b-gguf-q4_k_m
est. VRAM 22.8 GBon RTX 4090 · 24 GBJSON API →

Specifications

Parameters
27.0 B
Licence
apache-2.0
First seen on the Hub
2026-04-23
Base model
Qwen3.6-27B
Training datasets
undisclosed
Added to our catalog
2026-07-28

Family

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

Compare with any text-generation model