Benchmark result
Qwen3.8-27B-Ridge-3.7bpw on 2× NVIDIA GeForce RTX 5060 — 42.6 tok/s
Measured with llama.cpp b10884-434ddbbc0 on September 11, 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.
How this run compares
1st fastest of 2 runs of this model on 2× NVIDIA GeForce RTX 5060 · Multi-GPU · median 38.6 tok/s.
sort
- 142.6tok/s72.8llama.cppthis run
- 234.6tok/s81.2llama.cpp
Reproduce this run
toolllama.cpp b10884-434ddbbc0
modelQwen3.8-27B-Ridge-3.7bpw
context98,304
thinkingon
effortxhigh (model default)
samplingtemperature 0.20000000298023224 · top_p 0.8999999761581421 · top_k 0 · min_p 0.05000000074505806 · presence_penalty 0 · repeat_penalty 1
clientv0.4.59+97
Set those in llama.cpp, then:
llm-benchmark benchmark --model "Qwen3.8-27B-Ridge-3.7bpw" --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.