Benchmark result
Qwen3.8-27B-GSQ-RCO-IQ3_XXS on 2× NVIDIA GeForce RTX 5060 — 41.9 tok/s
Measured with llama.cpp b11785-8baabd53b on October 21, 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
1st fastest of 2 runs of this model on 2× NVIDIA GeForce RTX 5060 · Multi-GPU · median 40.6 tok/s.
sort
- 141.9tok/s85.3llama.cppthis run
- 239.2tok/s82.8llama.cpp
Reproduce this run
toolllama.cpp b11785-8baabd53b
modelQwen3.8-27B-GSQ-RCO-IQ3_XXS
context131,072
thinkingon
think limitnone
samplingtemperature 0.6000000238418579 · top_p 0.8999999761581421 · top_k 20 · min_p 0.10000000149011612 · presence_penalty 0 · repeat_penalty 1.0499999523162842
clientv0.4.96+102
Set those in llama.cpp, then:
llm-benchmark benchmark --model "Qwen3.8-27B-GSQ-RCO-IQ3_XXS" --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.