Benchmark result
Qwen3.8-27B-GSQ-RCO-IQ3_S on NVIDIA GeForce RTX 4080 SUPER — 72.1 tok/s
Measured with llama.cpp b10729-458681e1d on September 4, 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
4th fastest of 4 runs of this model on NVIDIA GeForce RTX 4080 SUPER · median 73.7 tok/s.
sort
- 174.9tok/s80.2llama.cpp
- 274.6tok/s84.3llama.cpp
- 372.8tok/s88.0llama.cpp
- 472.1tok/s82.6llama.cppthis run
Qwen3.8-27B-GSQ-RCO-IQ3_S on other hardware
Reproduce this run
toolllama.cpp b10729-458681e1d
modelQwen3.8-27B-GSQ-RCO-IQ3_S
context65,536
samplingtemperature 1 · top_p 0.949999988079071 · top_k 20 · min_p 0 · presence_penalty 0 · repeat_penalty 1
clientv0.4.55+97
Set those in llama.cpp, then:
llm-benchmark benchmark --model "Qwen3.8-27B-GSQ-RCO-IQ3_S" --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.