Model benchmarks
ornith:35b local LLM performance
As of July 2026, ornith:35b runs at up to 56.4 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).
OllamaQ4_K_M
Model size
34.7B
Peak speed
56.4 tok/s
Average speed
45.9 tok/s
Min memory
20.9 GB
Max context
180,000 tokens
Avg quality
66.9
Benchmark runs
2
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 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 | 61.0 | 66.9 | 72.7 |
| Agent Workflow | 15.7 | 42.4 | 69.1 |
| Code Generation | 64.7 | 69.3 | 73.9 |
| Role Play & Narrative | 74.9 | 81.6 | 88.3 |
| Research & Analysis | 68.5 | 74.1 | 79.7 |
Performance by hardware and tool
Every hardware/tool/quantization combination ornith:35b has been benchmarked on, ranked by peak token generation speed. Last updated July 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| AMD Radeon RX 7900 XTX | Ollama | Q4_K_M | 56.4 tok/s | 45.9 tok/s | 20.9 GB | 180,000 tokens | 66.9 | 2 |
Frequently asked questions
- Is ornith:35b good for coding?
- In our benchmarks, ornith:35b scores 69.3/100 for coding. It runs at about 45.9 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 ornith:35b good for agentic (tool-using) tasks?
- In our benchmarks, ornith:35b scores 42.4/100 for agentic workflows. It runs at about 45.9 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 ornith:35b for local inference?
- Across 2 community benchmark runs, ornith:35b reaches up to 56.4 tok/s and averages 45.9 tok/s, with the fastest results on AMD Radeon RX 7900 XTX.
- How much memory does ornith:35b need?
- The leanest observed configuration used about 20.9 GB of memory (quantizations tested: Q4_K_M).
- Which tools have been used to run ornith:35b?
- Benchmarks were submitted using Ollama. Results are community-contributed and updated as new runs arrive.