Qwen 3.6 27B and 35B MTP vs Standard on 16GB GPU
The article discusses the performance of Qwen 3.6 models with Multi-Token Prediction (MTP) on a 16GB GPU. It compares MTP-enabled variants to standard decoding, highlighting the trade-offs in speed and context size. The findings indicate that MTP can significantly enhance generation speed while affecting the average context window.
- ▪MTP is a form of speculative decoding that allows the model to propose several future tokens in a single step.
- ▪Testing was conducted on Qwen 3.6 27B and 35B models using an RTX 4080 with 16 GB VRAM.
- ▪MTP can deliver up to 67% faster generation speed at the cost of reducing the average context window.
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try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 3544400) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Rost Posted on May 24 • Originally published at glukhov.org Qwen 3.6 27B and 35B MTP vs Standard on 16GB GPU #selfhosting #llm #ai #llamacpp I tested Speculative decoding (Multi-Token Prediction, MTP) performance in Qwen 3.6 27B and 35B on an RTX 4080 with 16 GB VRAM. For a broader view of token speeds and VRAM trade-offs across more models on the same hardware, see 16 GB VRAM LLM benchmarks with llama.cpp.
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