Benchmark result
Qwen-AgentWorld-35B-A3B-UD-Q4_K_XL on Intel Graphics — 19.0 tok/s
Measured with llama.cpp manual on October 3, 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 Graphics · median 19.0 tok/s.
sort
- 119.1tok/s76.6llama.cpp · Q4_K
- 219.0tok/s73.3llama.cpp · Q4_Kthis run
Reproduce this run
toolllama.cpp manual
modelQwen-AgentWorld-35B-A3B-UD-Q4_K_XL (Q4_K)
context160,000
thinkingon
think limitnone
samplingtemperature 0.6000000238418579 · top_p 0.949999988079071 · top_k 20 · min_p 0 · presence_penalty 0 · repeat_penalty 1
clientv0.4.87+102
Set those in llama.cpp, then:
llm-benchmark benchmark --model "Qwen-AgentWorld-35B-A3B-UD-Q4_K_XL" --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.