Qwen 3.6 (27B, Q8)
Alibaba's Qwen 3.6 at 27B parameters, 8-bit quantization for higher fidelity than the Q4 build (at roughly double the memory footprint). Multimodal (text + image + video), 256K native context, explicit native tool-calling support. For machines with ~40GB+ memory.
At a glance
- Parameters
- 27B
- Quantization
- Q8_0
- Context window
- 262K tokens
- Approx. size
- 29.0 GB
- Engines
- llama.cpp, MLX
- License
- Apache-2.0 (open)
- Version
- v1.0.0 , released 2026-06-02
- Family
- qwen
Tuning
Defaults a gezel client applies out of the box, from real evaluation runs against this exact quantization.
- sampling.temperature
0.7- sampling.topP
0.8- sampling.topK
20- sampling.minP
0- sampling.maxTokens
8192- reasoning.thinkingBudget
4096- reasoning.enableThinking
true- profiles
- thinking-general, thinking-coding, thinking-precise, instruct, creative
Model behaviors
Client-side behavior modules the catalog enables for this model (reasoning-tag handling, fabrication detection, prompt shaping).
- reasoning.strip-think-tags
- mcp.compact-tool-schemas
- fabrication.detect-past-tense-no-tools
- turn.ollama-num-predict-bumped
- turn.preamble-folding
- turn.ramble-detection
- tools.mlx-grammar
- prompt.derive-by-execution
Sources
- llama.cpp (GGUF)
- lmstudio-community/Qwen3.6-27B-GGUF ·
Qwen3.6-27B-Q8_0.gguf· Q8_0 - MLX
- mlx-community/Qwen3.6-27B-8bit
- Upstream
- https://ollama.com/library/qwen3.6
- Manifest
- View on GitHub
Tags
- alibaba
- multimodal
- vision
- video
- tools
- long-context