ababb123/Qwen3.6-27B-Balanced

Thinking mode (default) — general tasks:

• temperature=1.0, top_p=0.95, top_k=20, min_p=0.0, presence_penalty=0.0, repetition_penalty=1.0

Thinking mode — precise coding / WebDev:

• temperature=0.6, top_p=0.95, top_k=20, min_p=0.0, presence_penalty=0.0, repetition_penalty=1.0

Non-thinking (Instruct) mode:

• temperature=0.7, top_p=0.80, top_k=20, min_p=0.0, presence_penalty=1.5, repetition_penalty=1.0

My personal preference for coding: temperature=0.6 with presence_penalty=1.5. Slightly lower temp keeps tool-call formatting tight; presence 1.5 keeps thinking from spiraling in long agent loops.

Important:

• Keep at least 128K context to preserve thinking capabilities
• Recommended output length: 32,768 tokens for most queries, up to 81,920 for competition-tier math/code
• Use --jinja with llama.cpp for proper chat template handling
• Vision support requires the mmproj file alongside the main GGUF
• YaRN rope scaling is static in llama.cpp and can hurt short-context performance — only modify rope_parameters if you actually need >262K context

Prompting tip: this model is a bit more sensitive to prompt clarity than Qwen3.5-35B-A3B. For agentic flows, spell out format, constraints, and scope in the system prompt — it'll stay on rails much better than with vague instructions.

Turning Thinking On/Off

Qwen3.6 ships with thinking on by default. Turn it off when you want faster, shorter replies and don't need chain-of-thought.

Heads up: Qwen3.6 does not support the /think and /no_think soft switches that Qwen3 had. You must use the chat-template kwarg below.

LM Studio

1. Load the model
2. Right-side settings panel → Model Settings → Prompt Template (or Chat Template Options)
3. Set enable_thinking to false in the template kwargs
4. Some LM Studio versions expose this as a direct "Reasoning" / "Thinking" toggle — same effect

llama.cpp

llama-server — set as default for all requests:

llama-server -m Qwen3.6-27B-Uncensored-HauhauCS-Balanced-Q4_K_P.gguf \
  --mmproj mmproj-Qwen3.6-27B-Uncensored-HauhauCS-Balanced-f16.gguf \
  --jinja -c 131072 -ngl 99 \
  --chat-template-kwargs '{"enable_thinking": false}'

Per-request via the OpenAI-compatible API:

{
  "model": "qwen3.6-27b",
  "messages": [{"role": "user", "content": "..."}],
  "chat_template_kwargs": {"enable_thinking": false}
}

Python openai SDK:

client.chat.completions.create(
    model="qwen3.6-27b",
    messages=[{"role": "user", "content": "..."}],
    extra_body={"chat_template_kwargs": {"enable_thinking": False}},
)

Agent scenarios — keep reasoning in context across turns (this one's important):

{"chat_template_kwargs": {"preserve_thinking": true}}

This retains the reasoning block in chat history. Useful for agents where reasoning consistency across tool-call loops matters.

Usage

Works with llama.cpp, LM Studio, Jan, koboldcpp, and other GGUF-compatible runtimes.

llama-cli -m Qwen3.6-27B-Uncensored-HauhauCS-Balanced-Q4_K_P.gguf \
  --mmproj mmproj-Qwen3.6-27B-Uncensored-HauhauCS-Balanced-f16.gguf \
  --jinja -c 131072 -ngl 99