110 tok/s with 12GB VRAM on Qwen3.6 35B A3B and ik_llama.cpp

Had been getting great MTP performance with llama.cpp on my RTX 4070 Super 12GB until they merged the MTP PR. Performance tanked…

By Vane May 21, 2026 1 min read
110 tok/s with 12GB VRAM on Qwen3.6 35B A3B and ik_llama.cpp

Had been getting great MTP performance with llama.cpp on my RTX 4070 Super 12GB until they merged the MTP PR. Performance tanked and was barely above non-MTP. I then decided to try out ik_llama.cpp since it also supports MTP and is apparently better optimized for CPU offloading.

Key Takeaways

  • Switching from llama.cpp to ik_llama.cpp resulted in a 110.24 tok/s average, or a 22% increase.
  • To achieve similar results on a 12GB RTX GPU using ik_llama.cpp, ensure you use the provided launch parameters:
  • llama-server \
    -m Qwen3.6-35B-A3B-IQ4_XS-4.19bpw.gguf \
    --fit \
    --fit-margin 1664 \
    --ctx-size 131072 \
    --cache-type-k q8_0 \
    --cache-type-v q8_0 \
    --cache-type-k-draft q8_0 \
    --cache-type-v-draft q8_0 \
    --multi-token-prediction \
    --draft-p-min 0.75 \
    --draft-max 3 \
    --no-mmap \
    --mlock \
    --threads 8 \
    --temp 0.0
    
  • If you encounter an OOM error, try increasing the –fit-margin to 1792 or even 2048.

I am running my GPU as a secondary GPU with CachyOS and can use all available VRAM. If you get an OOM error when loading the model, consider adjusting these parameters accordingly.

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