Model benchmarks
prism-ml/Ternary-Bonsai-8B-gguf:Q2_0 local LLM performance
As of October 2026, prism-ml/Ternary-Bonsai-8B-gguf:Q2_0 runs at up to 153.3 tok/s for local inference (best of 3 community benchmark runs across 1 GPU).
Model size
8B
Peak speed
153.3 tok/s
Average speed
151.1 tok/s
Avg PP
1180.2 tok/s
Min memory
7.6 GB
Max context
65,536 tokens
Avg output / run
7,302 tokens
Avg runtime / run
52s
Avg quality
48.5
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 | 42.5 | 48.5 | 55.4 |
| Agent Workflow | 48.9 | 64.1 | 78.0 |
| Code Generation | 10.9 | 21.2 | 29.9 |
| Role Play & Narrative | 49.3 | 67.7 | 79.1 |
| Research & Analysis | 34.6 | 41.1 | 46.2 |
Performance by hardware and tool
Every hardware/tool/quantization combination prism-ml/Ternary-Bonsai-8B-gguf:Q2_0 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 4070 | llama.cpp | Q2_0 | 153.3 tok/s | 151.1 tok/s | 7.6 GB | 65,536 tokens | 48.5 | 3 |
Benchmark runs
All 3 prism-ml/Ternary-Bonsai-8B-gguf:Q2_0 runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- How fast is prism-ml/Ternary-Bonsai-8B-gguf:Q2_0 for local inference?
- Across 3 community benchmark runs, prism-ml/Ternary-Bonsai-8B-gguf:Q2_0 reaches up to 153.3 tok/s and averages 151.1 tok/s, with the fastest results on NVIDIA GeForce RTX 4070.
- How much memory does prism-ml/Ternary-Bonsai-8B-gguf:Q2_0 need?
- The leanest observed configuration used about 7.6 GB of memory (quantizations tested: Q2_0).
- Which tools have been used to run prism-ml/Ternary-Bonsai-8B-gguf:Q2_0?
- Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.