Benchmark result
Ternary-Bonsai-2-27B-PQ2_0 on 2× NVIDIA GeForce RTX 5060 — 41.4 tok/s
Measured with llama.cpp b10706-1a07bfa5f on September 18, 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
2nd fastest of 2 runs of this model on 2× NVIDIA GeForce RTX 5060 · Multi-GPU · median 41.6 tok/s.
sort
- 141.8tok/s43.8llama.cpp · Q2_0
- 241.4tok/s78.5llama.cpp · Q2_0this run
Ternary-Bonsai-2-27B-PQ2_0 on other hardware
Reproduce this run
toolllama.cpp b10706-1a07bfa5f
modelTernary-Bonsai-2-27B-PQ2_0 (Q2_0)
context131,072
thinkingon
effortxhigh (model default)
samplingtemperature 0.699999988079071 · top_p 0.949999988079071 · top_k 20 · min_p 0 · presence_penalty 0 · repeat_penalty 1.0499999523162842
clientv0.4.59+97
Set those in llama.cpp, then:
llm-benchmark benchmark --model "Ternary-Bonsai-2-27B-PQ2_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.