Qwen 3.6 27B Achieves 2.5x Faster Local Inference via MTP With 262k Context on 48GB

MTP Comes to Qwen 3.6 27B

A new post on r/LocalLLaMA has detailed how to achieve 2.5x faster inference with Qwen 3.6 27B using a new MTP support PR for llama.cpp. The guide, tested on an M2 Max 96GB, earned over 600 upvotes from the community.

Key Capabilities

Beyond the 2.5x speed improvement via speculative decoding, this configuration enables 262,000-token context windows on 48GB of memory. It includes a fixed chat template, drop-in compatibility with OpenAI and Anthropic API endpoints, and q4_0 KV cache compression.

Finally Viable for Local Agentic Coding

The author describes this as "finally a viable option for local agentic coding." The combination of long context and fast inference makes Qwen 3.6 27B a practical local alternative to cloud APIs for agentic workflows like Claude Code or Cursor.

Caveats

The relevant llama.cpp PR remains unstable with ongoing discussions. The author revised their original recommendations after discovering build instability, replacing turbo quants with standard q4_0 KV cache compression. Wait for the upload confirmation before downloading from Hugging Face.