Model benchmarks
prism-ml/bonsai-27b local LLM performance
As of August 2026, prism-ml/bonsai-27b runs at up to 83.7 tok/s for local inference (best of 2 community benchmark runs across 2 GPUs).
Model size
27B
Peak speed
83.7 tok/s
Average speed
49.0 tok/s
Min memory
4.4 GB
Max context
16,384 tokens
Avg output / run
19,242 tokens
Avg runtime / run
13m 46s
Avg quality
74.1
Benchmark runs
2
GPUs tested
2
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, across all 2 runs. 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 | 67.7 | 74.1 | 80.4 |
| Agent Workflow | 67.5 | 78.3 | 89.1 |
| Code Generation | 49.1 | 60.3 | 71.6 |
| Role Play & Narrative | 77.9 | 84.9 | 91.8 |
| Research & Analysis | 69.3 | 72.8 | 76.3 |
Performance by hardware and tool
Every hardware/tool/quantization combination prism-ml/bonsai-27b has been benchmarked on, ranked by peak token generation speed. Last updated August 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| NVIDIA GeForce RTX 4070 Ti SUPER | LM Studio | — | 83.7 tok/s | 83.7 tok/s | 4.4 GB | 16,384 tokens | 67.0 | 1 |
| Apple M5 | LM Studio | — | 14.3 tok/s | 14.3 tok/s | 13.2 GB | 8,192 tokens | 81.1 | 1 |
Frequently asked questions
- Is prism-ml/bonsai-27b good for coding?
- In our benchmarks, prism-ml/bonsai-27b scores 60.3/100 for coding. It runs at about 49.0 tok/s, so if you want more speed, Gemma4:E2B/QAT-MTP@131K is faster (~303.9 tok/s) and still scores well for coding (66.9/100).
- Is prism-ml/bonsai-27b good for agentic (tool-using) tasks?
- In our benchmarks, prism-ml/bonsai-27b scores 78.3/100 for agentic workflows. It runs at about 49.0 tok/s, so if you want more speed, Gemma4:E2B/QAT-MTP@131K is faster (~303.9 tok/s) and still scores well for agentic workflows (71.7/100).
- How fast is prism-ml/bonsai-27b for local inference?
- Across 2 community benchmark runs, prism-ml/bonsai-27b reaches up to 83.7 tok/s and averages 49.0 tok/s, with the fastest results on NVIDIA GeForce RTX 4070 Ti SUPER.
- How much memory does prism-ml/bonsai-27b need?
- The leanest observed configuration used about 4.4 GB of memory.
- Which tools have been used to run prism-ml/bonsai-27b?
- Benchmarks were submitted using LM Studio. Results are community-contributed and updated as new runs arrive.