Draft acceptance tweaks?

What can I do to get more from MTP if anything? It am I sitting at the expected range. Thanks /opt/llama.cpp/build/bin/llama-server --host 10.210.44.126 --port 11434 --model /opt/models/Qwen3.6-35B-A3B-MTP-UD-Q8_K_XL.gguf --mmproj /opt/models/mmproj-35B-A3B-BF16.gguf --ctx-size 100352 --cache-type-k f16 --cache-type-v f16 --gpu-layers 999 --main-gpu 1 --poll 0 --batch-size 1024 --ubatch-size 256 --threads 6 --split-mode tensor --tensor-split 34,40,26 --jinja --reasoning-format deepseek --image-min-tokens 1024 --alias Qwen3.6-35B-MTP-Q8-XL,frigate --flash-attn on --reasoning on --spec-type draft-mtp --spec-draft-n-max 5 --ctx-checkpoints 48 --cont-batching --min-p 0.05 --top-p 0.80 --parallel 2 --metrics --kv-unified --temp 0.6 --top-k 20 --load-mode none --lazy-mode off --fit off --slots submitted by /u/Bulky-Priority6824 [link] [comments]

Extremely slow DSpark draft model performance (1-2 t/s) with DeepSeek-V4-Flash on llama-server compared to MTP?
3 days benchmarking most llama.cpp flags on my weird 40gb vram laptop + tb4 egpu setup. Got +70% generation, +40% prefill, 60k more context, and filed a bug in llama around MTP. What I learned.
Tested Nemotron 3.5 Lightning locally on coding, Hermes Agent and agentic work

Source: r/LocalLLaMA | 2026-09-07

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