Model benchmarks
prism-ml/Ternary-Bonsai-2-27B-gguf local LLM performance
As of September 2026, prism-ml/Ternary-Bonsai-2-27B-gguf runs at up to 47.9 tok/s for local inference (best of 3 community benchmark runs across 1 GPU).
Model size
27B
Peak speed
47.9 tok/s
Average speed
46.5 tok/s
Avg PP
848.7 tok/s
Min memory
11.4 GB
Max context
30.720 tokens
Avg output / run
44.432 tokens
Avg runtime / run
16m 29s
Avg quality
55.6
Benchmark runs
3
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, across all 3 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 | 42.1 | 55.6 | 70.7 |
| Agent Workflow | 76.7 | 82.9 | 89.6 |
| Code Generation | 2.0 | 16.9 | 29.5 |
| Role Play & Narrative | 86.8 | 87.7 | 89.1 |
| Research & Analysis | 1.6 | 34.9 | 81.4 |
Performance by hardware and tool
Every hardware/tool/quantization combination prism-ml/Ternary-Bonsai-2-27B-gguf has been benchmarked on, ranked by peak token generation speed. Last updated September 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| NVIDIA GeForce RTX 4070 | Unsloth Studio | — | 47.9 tok/s | 47.9 tok/s | 11.4 GB | 16.384 tokens | 40.8 | 1 |
| NVIDIA GeForce RTX 4070 | Unsloth Studio | TQ1_0 | 46.4 tok/s | 45.8 tok/s | 11.4 GB | 30.720 tokens | 63.0 | 2 |
Benchmark runs
All 3 prism-ml/Ternary-Bonsai-2-27B-gguf runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is prism-ml/Ternary-Bonsai-2-27B-gguf good for coding?
- In our benchmarks, prism-ml/Ternary-Bonsai-2-27B-gguf scores 16.9/100 for coding. It runs at about 46.5 tok/s, so if you want more speed, local-qwen is faster (~60.2 tok/s) and still scores well for coding (84.8/100).
- Is prism-ml/Ternary-Bonsai-2-27B-gguf good for agentic (tool-using) tasks?
- In our benchmarks, prism-ml/Ternary-Bonsai-2-27B-gguf scores 82.9/100 for agentic workflows. It runs at about 46.5 tok/s, so if you want more speed, granite-4.2-8b-Q4_K_L is faster (~71.6 tok/s) and still scores well for agentic workflows (92.9/100).
- How fast is prism-ml/Ternary-Bonsai-2-27B-gguf for local inference?
- Across 3 community benchmark runs, prism-ml/Ternary-Bonsai-2-27B-gguf reaches up to 47.9 tok/s and averages 46.5 tok/s, with the fastest results on NVIDIA GeForce RTX 4070.
- How much memory does prism-ml/Ternary-Bonsai-2-27B-gguf need?
- The leanest observed configuration used about 11.4 GB of memory (quantizations tested: TQ1_0).
- Which tools have been used to run prism-ml/Ternary-Bonsai-2-27B-gguf?
- Benchmarks were submitted using Unsloth Studio. Results are community-contributed and updated as new runs arrive.