Benchmark result
PentaCoder-9B-Q8_0 on NVIDIA GeForce RTX 5070 Ti — 66.2 tok/s
Measured with llama.cpp b11200-81bc6b83f on October 2, 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 NVIDIA GeForce RTX 5070 Ti · median 70.3 tok/s.
sort
- 174.4tok/s74.6llama.cpp · Q8_0
- 266.2tok/s75.2llama.cpp · Q8_0this run
Reproduce this run
toolllama.cpp b11200-81bc6b83f
modelPentaCoder-9B-Q8_0 (Q8_0)
context65,536
thinkingon
samplingtemperature 0.6000000238418579 · top_p 0.949999988079071 · top_k 20 · min_p 0.05000000074505806 · presence_penalty 0 · repeat_penalty 1
clientv0.4.85+101
Set those in llama.cpp, then:
llm-benchmark benchmark --model "PentaCoder-9B-Q8_0" --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.