Benchmark result
ISTA-DASLab/Qwen3.8-27B-GSQ-RCO-GGUF:IQ3_XXS-mtp on AMD Radeon RX 9070/9070 XT/9070 GRE — 44.5 tok/s
Measured with llama.cpp b11388-050439614 on October 5, 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 5 runs of this model on AMD Radeon RX 9070/9070 XT/9070 GRE · median 44.1 tok/s.
sort
- 146.3tok/s79.3llama.cpp
- 244.5tok/s87.0llama.cppthis run
- 344.1tok/s85.6llama.cpp
- 442.5tok/s72.5llama.cpp
- 534.5tok/s81.7Ollama · IQ3_S
Reproduce this run
toolllama.cpp b11388-050439614
modelISTA-DASLab/Qwen3.8-27B-GSQ-RCO-GGUF:IQ3_XXS-mtp
context32,768
thinkingon
effortxhigh (model default)
think limit6,144 tokens
samplingtemperature 0.699999988079071 · top_p 0.949999988079071 · top_k 20 · min_p 0.10000000149011612 · presence_penalty 0 · repeat_penalty 1
clientv0.4.87+102
Set those in llama.cpp, then:
llm-benchmark benchmark --model "ISTA-DASLab/Qwen3.8-27B-GSQ-RCO-GGUF:IQ3_XXS-mtp" --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.