Model benchmarks
ternary-bonsai-2-2b local LLM performance
As of October 2026, ternary-bonsai-2-2b runs at up to 40.0 tok/s for local inference (best of 4 community benchmark runs across 1 GPU).
Model size
2B
Peak speed
40.0 tok/s
Average speed
39.1 tok/s
Avg PP
774.3 tok/s
Min memory
2.1 GB
Max context
65,536 tokens
Avg output / run
13,058 tokens
Avg runtime / run
6m 34s
Avg quality
35.3
Benchmark runs
4
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 4 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 | 30.3 | 35.3 | 42.8 |
| Agent Workflow | 21.3 | 39.7 | 67.3 |
| Code Generation | 8.8 | 12.3 | 15.0 |
| Role Play & Narrative | 55.3 | 58.6 | 62.2 |
| Research & Analysis | 24.0 | 30.5 | 37.2 |
Performance by hardware and tool
Every hardware/tool/quantization combination ternary-bonsai-2-2b 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 GTX 1050 | LM Studio | Q2_0 | 40.0 tok/s | 39.1 tok/s | 2.1 GB | 65,536 tokens | 35.3 | 4 |
Benchmark runs
All 4 ternary-bonsai-2-2b runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is ternary-bonsai-2-2b good for coding?
- In our benchmarks, ternary-bonsai-2-2b scores 12.3/100 for coding. It runs at about 39.1 tok/s, so if you want more speed, nvidia/Qwen3.8-27B-NVFP4 is faster (~63.3 tok/s) and still scores well for coding (82.7/100).
- Is ternary-bonsai-2-2b good for agentic (tool-using) tasks?
- In our benchmarks, ternary-bonsai-2-2b scores 39.7/100 for agentic workflows. It runs at about 39.1 tok/s, so if you want more speed, Nex-N2.5-mini-APEX-Mini is faster (~88.2 tok/s) and still scores well for agentic workflows (91.3/100).
- How fast is ternary-bonsai-2-2b for local inference?
- Across 4 community benchmark runs, ternary-bonsai-2-2b reaches up to 40.0 tok/s and averages 39.1 tok/s, with the fastest results on NVIDIA GeForce GTX 1050.
- How much memory does ternary-bonsai-2-2b need?
- The leanest observed configuration used about 2.1 GB of memory (quantizations tested: Q2_0).
- Which tools have been used to run ternary-bonsai-2-2b?
- Benchmarks were submitted using LM Studio. Results are community-contributed and updated as new runs arrive.