Qwen deployment comparison: Ollama vs vLLM vs MLX¶
The Qwen deployment comparison analyzes the trade-offs between Ollama, vLLM, and MLX when running the Qwen 3.6 27B model, particularly for Coding Agent workflows^[001-TODO__Qwen_3.6_27B_—_面向_Coding_Agent_的开源模型.md].
High-Level Comparison¶
| Feature | Ollama | vLLM | MLX |
|---|---|---|---|
| Qwen 3.6 27B Support | ❌ No (Only 35B A3B1)^[001-TODO__Qwen_3.6_27B_—_面向_Coding_Agent_的开源模型.md] | ✅ Full Support^[001-TODO__Qwen_3.6_27B_—_面向_Coding_Agent_的开源模型.md] | ⏳ Upcoming^[001-TODO__Qwen_3.6_27B_—_面向_Coding_Agent_的开源模型.md] |
| Setup Difficulty | ⭐ Simple^[001-TODO__Qwen_3.6_27B_—_面向_Coding_Agent_的开源模型.md] | ⭐⭐ Moderate^[001-TODO__Qwen_3.6_27B_—_面向_Coding_Agent_的开源模型.md] | ⭐⭐ Moderate^[001-TODO__Qwen_3.6_27B_—_面向_Coding_Agent_的开源模型.md] |
| Recommended Scenario | Quick trial / Not strict on 27B^[001-TODO__Qwen_3.6_27B_—_面向_Coding_Agent_的开源模型.md] | Formal Agent Workflows^[001-TODO__Qwen_3.6_27B_—_面向_Coding_Agent_的开源模型.md] | Apple Silicon Native^[001-TODO__Qwen_3.6_27B_—_面向_Coding_Agent_的开源模型.md] |
Deployment Specifics¶
Ollama¶
Ollama is the simplest option for getting started, but as of the documented date (2026-04-23), it does not support the 27B model variant^[001-TODO__Qwen_3.6_27B_—_面向_Coding_Agent_的开源模型.md].
- Availability: Only the 35B A3B1 variant is available^[001-TODO__Qwen_3.6_27B_—_面向_Coding_Agent_的开源模型.md].
- Use Case: Best for users who want a quick trial and are not specifically focused on the 27B parameter architecture^[001-TODO__Qwen_3.6_27B_—_面向_Coding_Agent_的开源模型.md].
vLLM¶
vLLM is the current best choice for deploying Qwen 3.6 27B, especially for Agentic Coding tasks^[001-TODO__Qwen_3.6_27B_—_面向_Coding_Agent_的开源模型.md]. It offers full support and compatibility with major agent frameworks like Hermes Agent.
Recommended Configuration¶
To utilize the model's capabilities (especially native tool calling), specific flags are required^[001-TODO__Qwen_3.6_27B_—_面向_Coding_Agent_的开源模型.md]:
vllm serve Qwen/Qwen3-27B \
--port 8000 \
--tensor-parallel-size 1 \
--max-model-len 32768 \
--enable-auto-tool-choice \
--tool-call-parser qwen3
Critical Parameters¶
--enable-auto-tool-choice: Must be enabled. Without this, the model will only describe tool usage ("text") rather than executing the tool calls^[001-TODO__Qwen_3.6_27B_—_面向_Coding_Agent_的开源模型.md].--max-model-len: Should be set to the maximum hardware-allowed value. Long context is a core advantage of Qwen 3.6^[001-TODO__Qwen_3.6_27B_—_面向_Coding_Agent_的开源模型.md].--tool-call-parser: Must be set toqwen3to match the model version format^[001-TODO__Qwen_3.6_27B_—_面向_Coding_Agent_的开源模型.md].
MLX¶
MLX is intended for Apple Silicon users who want to run models natively on Mac hardware^[001-TODO__Qwen_3.6_27B_—_面向_Coding_Agent_的开源模型.md].
- Status: Support for Qwen 3.6 27B is upcoming^[001-TODO__Qwen_3.6_27B_—_面向_Coding_Agent_的开源模型.md].
Summary & Recommendations¶
- For Qwen 3.6 27B: Use vLLM. It is currently the only option that fully supports this specific model variant with the necessary features for coding agents^[001-TODO__Qwen_3.6_27B_—_面向_Coding_Agent_的开源模型.md].
- For Quick Testing: Ollama (if using the 35B A3B1 variant is acceptable)^[001-TODO__Qwen_3.6_27B_—_面向_Coding_Agent_的开源模型.md].
- For Mac Users: Wait for MLX support^[001-TODO__Qwen_3.6_27B_—_面向_Coding_Agent_的开源模型.md].
Related Concepts¶
- [[Qwen 3.6 27B — 面向 Coding Agent 的开源模型]]
- Hermes Agent
- 20/80 Learning Principle
Sources¶
001-TODO__Qwen_3.6_27B_—_面向_Coding_Agent_的开源模型.md