Fixed jinja chat templates for Qwen 3.5 & 3.6 (v20)

This is a drop-in Jinja template that fixes rendering errors, KV cache invalidation, token waste, and fatal agentic stalling in the official Qwen chat templates.

It is tested to work across LM Studio, llama.cpp, vLLM, MLX, oMLX, and any engine that supports HuggingFace Jinja templates.

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Why you need this

The official Qwen templates contain restrictions and Python-specific Jinja logic that break usage on many inference engines and agent frameworks.

Here are the critical issues this template fixes:

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Quick install

Choose your environment and update the template:

LM Studio

1. Open your Qwen model in the right-side panel.
2. Scroll down to Prompt Template.
3. Replace the template with the contents of chat_template.jinja.
4. Click Save.

llama.cpp / koboldcpp

--jinja --chat-template-file chat_template.jinja

vLLM

Replace the "chat_template" string in your tokenizer_config.json with the raw file contents. Use the qwen3_coder tool parser:

--tool-call-parser qwen3_coder

oMLX

Overwrite chat_template.jinja in your local model directory. Load with --jinja. Remove any chat_template_kwargs overrides because the template handles everything internally.

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Which file do I use?

Both Qwen 3.5 and Qwen 3.6 variants (including 35B, 32B, 27B, and 14B parameters) have been consolidated. You only need the single chat_template.jinja file at the root of the repository.

One-line versions (chat_template_oneline.txt) are pre-minified for engines that require a single-line template string.

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The thinking toggle

You can control the model reasoning behavior. Insert <|think_on|> or <|think_off|> anywhere in your system or user prompt.

The template natively intercepts the tag, removes it from the final context so the model never sees it, and flips the reasoning mode instantly.

Fast answer, no reasoning:

System: You are a coding assistant. <|think_off|>
User: What's 2+2?

Deep reasoning:

System: You are a coding assistant. <|think_on|>
User: Implement a red-black tree in Rust.

(The tag syntax uses Qwen's control-token delimiters to guarantee it will never collide with legitimate text or file paths, unlike earlier community templates that used /think)

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Token Saving: Stripping past thoughts

By default in v19, this template preserves all past <think> blocks in the chat history. This is intentional: it prevents the model from suffering "amnesia stalls" during complex, multi-step agentic loops, and it mathematically guarantees a 100% Prefix KV Cache hit rate on local inference engines.

However, if you are running constrained hardware and need to save context tokens, you can explicitly disable this feature in your engine's template kwargs to automatically strip past thoughts:

{
 "preserve_thinking": false
}

(Note: Setting this to false will naturally reduce your KV Cache hit rate during multi-turn chats, as the prompt string will dynamically mutate).

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Running the test suite

python3 scripts/test_v20.py

Tests cover: auto_disable_thinking_with_tools, payload truncation logic, parallel tool spacing, mid-conversation system rendering, deep agent loop fallback, XML tool format, <|think_off|> / <|think_on|> inline overrides, and all legacy v19 regression tests.

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Authorship

License

Apache-2.0, inherited from Qwen.

Rewritten Jinja templates fixing 5 bugs in official Qwen 3.5/3.6. Works in LM Studio, llama.cpp, MLX, vLLM. • 1 item • Updated Apr 30 • 4