Model benchmarks
bonsai-2-27b local LLM performance
As of October 2026, bonsai-2-27b runs at up to 39.2 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).
Model size
27B
Peak speed
39.2 tok/s
Average speed
38.7 tok/s
Avg PP
271.8 tok/s
Min memory
6.9 GB
Max context
8,192 tokens
Avg output / run
16,820 tokens
Avg runtime / run
7m 33s
Avg quality
n/a
Benchmark runs
2
GPUs tested
1
Quality by task
Average LLM-judged quality (0–100) with the run-to-run spread shown as a P5–P95 band, overall and for each benchmark task. The low and high columns show how much the judge’s score varies between runs, and need at least two runs to display.
| Task | P5 (low) | Avg | P95 (high) |
|---|---|---|---|
| Overall | — | n/a | — |
| Agent Workflow | — | n/a | — |
| Code Generation | — | n/a | — |
| Role Play & Narrative | — | n/a | — |
| Research & Analysis | — | n/a | — |
Performance by hardware and tool
Every hardware/tool/quantization combination bonsai-2-27b has been benchmarked on, ranked by peak token generation speed. Last updated October 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| NVIDIA GeForce RTX 2070 SUPER | llama-server | — | 39.2 tok/s | 39.2 tok/s | 6.9 GB | 8,192 tokens | n/a | 1 |
| NVIDIA GeForce RTX 2070 SUPER | llama-server (Bonsai 2 27B PTQ1_0) | — | 38.3 tok/s | 38.3 tok/s | 6.9 GB | 8,192 tokens | n/a | 1 |
Benchmark runs
All 2 bonsai-2-27b runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- How fast is bonsai-2-27b for local inference?
- Across 2 community benchmark runs, bonsai-2-27b reaches up to 39.2 tok/s and averages 38.7 tok/s, with the fastest results on NVIDIA GeForce RTX 2070 SUPER.
- How much memory does bonsai-2-27b need?
- The leanest observed configuration used about 6.9 GB of memory.
- Which tools have been used to run bonsai-2-27b?
- Benchmarks were submitted using llama-server, llama-server (Bonsai 2 27B PTQ1_0). Results are community-contributed and updated as new runs arrive.