Benchmark result
unsloth/Qwen3.5-9B-GGUF on Intel(R) Arc(TM) 140V GPU (16GB) — 13.3 tok/s
Measured with llama.cpp unsloth-studio/v0.1.810-beta on September 18, 2026.
What the model built
Open full screen →The coding scenario asks for a playable game in a single HTML file. This is exactly what the model returned, unedited; the frame only adds a line that tells this page how tall it is.
How this run compares
2nd fastest of 2 runs of this model on Intel(R) Arc(TM) 140V GPU (16GB) · median 13.5 tok/s.
sort
- 113.8tok/s71.8Unsloth Studio · UD-Q4_K_XL · KV q8_0
- 213.3tok/s67.4llama.cppthis run
Reproduce this run
toolllama.cpp unsloth-studio/v0.1.810-beta
modelunsloth/Qwen3.5-9B-GGUF
context16,384
samplingtemperature 0.800000011920929 · top_p 0.949999988079071 · top_k 40 · min_p 0.05000000074505806 · presence_penalty 0 · repeat_penalty 1
clientv0.4.59+97
Set those in llama.cpp, then:
llm-benchmark benchmark --model "unsloth/Qwen3.5-9B-GGUF" --tool "llama.cpp"The client prompts for context length and thinking mode, and for the KV cache dtype on Unsloth Studio. Sampling is left at the model default — the values above are what the tool reported using, not overrides the client sent.