Model benchmarks
ornith-1.0-35b local LLM performance
As of August 2026, ornith-1.0-35b runs at up to 47.8 tok/s for local inference (best of 2 community benchmark runs across 2 GPUs).
LM Studio
Model size
35B
Peak speed
47.8 tok/s
Average speed
34.6 tok/s
Min memory
19.7 GB
Max context
8,192 tokens
Avg output / run
13,258 tokens
Avg runtime / run
5m 15s
Avg quality
80.9
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 | 79.4 | 80.9 | 82.4 |
| Agent Workflow | 80.3 | 82.7 | 85.1 |
| Code Generation | 74.8 | 78.2 | 81.6 |
| Role Play & Narrative | 83.1 | 85.9 | 88.7 |
| Research & Analysis | 72.7 | 76.9 | 81.1 |
Performance by hardware and tool
Every hardware/tool/quantization combination ornith-1.0-35b 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 |
|---|---|---|---|---|---|---|---|---|
| Apple M2 Max | LM Studio | — | 47.8 tok/s | 47.8 tok/s | 27.1 GB | 8,192 tokens | 82.6 | 1 |
| NVIDIA GeForce RTX 4070 Ti SUPER | LM Studio | — | 21.3 tok/s | 21.3 tok/s | 19.7 GB | 8,192 tokens | 79.3 | 1 |
Frequently asked questions
- Is ornith-1.0-35b good for coding?
- In our benchmarks, ornith-1.0-35b scores 78.2/100 for coding. It runs at about 34.6 tok/s, so if you want more speed, Tiel-Coder-35B-A3B-MLX-oQ4e-MTP is faster (~123.6 tok/s) and still scores well for coding (76.5/100).
- Is ornith-1.0-35b good for agentic (tool-using) tasks?
- In our benchmarks, ornith-1.0-35b scores 82.7/100 for agentic workflows. It runs at about 34.6 tok/s, so if you want more speed, openai/gpt-oss-20b:2 is faster (~154.8 tok/s) and still scores well for agentic workflows (87.2/100).
- How fast is ornith-1.0-35b for local inference?
- Across 2 community benchmark runs, ornith-1.0-35b reaches up to 47.8 tok/s and averages 34.6 tok/s, with the fastest results on Apple M2 Max.
- How much memory does ornith-1.0-35b need?
- The leanest observed configuration used about 19.7 GB of memory.
- Which tools have been used to run ornith-1.0-35b?
- Benchmarks were submitted using LM Studio. Results are community-contributed and updated as new runs arrive.