Llama.cpp MTP with Qwen3.6 27B on Headless RTX 3090

Saw some posts around PP being slower, so they were cautious on trying it.

Here’s a real-world datapoint.

Settings:

• Headless RTX 3090 24G
• OpenCode
• Model unsloth’s Qwen3.6-27B-MTP-Q4_K_M.gguf
• 128k context
• q8_0 kv cache
• –spec-draft-n-max: 3
• –draft-p-min: 0

Use Cases:

• Research task that uses ~85,000 tokens
• Coding task that uses ~85,000 tokens.

Without MTP (llama.cpp:server-cuda13-b9174):

• PP: 1,050 tok/s
• TG: 27 toks/s
• Total time to complete 85k tokens: ~39 mins

With MTP (latest master fork):

• PP: 600 tok/s (down 42%)
• TG: 50 tok/s (up 85%)
• Total time to complete 85k tokens: ~23 mins (1.7x faster or 41% reduction)

A 41% time savings is quite huge, so unless you’re PP heavy, I’d recommend giving MTP a try on your use cases! I have it on a dual agent set-up so your total processing times may be better since I have another critic agent check the main agent’s work.