Model benchmarks
Ornith-1.5-9B-oQ8e local LLM performance
As of August 2026, Ornith-1.5-9B-oQ8e runs at up to 53.1 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).
Model size
9B
Peak speed
53.1 tok/s
Average speed
53.0 tok/s
Min memory
11.5 GB
Max context
262,144 tokens
Avg runtime / run
24m 59s
Avg quality
65.6
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 | 61.3 | 65.6 | 70.0 |
| Agent Workflow | 69.0 | 70.5 | 72.0 |
| Code Generation | 7.8 | 21.0 | 34.1 |
| Role Play & Narrative | 85.5 | 87.5 | 89.6 |
| Research & Analysis | 82.9 | 83.6 | 84.2 |
Performance by hardware and tool
Every hardware/tool/quantization combination Ornith-1.5-9B-oQ8e 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 M5 Max | oMLX | — | 53.1 tok/s | 53.0 tok/s | 11.5 GB | 262,144 tokens | 65.6 | 2 |
Benchmark runs
All 2 Ornith-1.5-9B-oQ8e runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is Ornith-1.5-9B-oQ8e good for coding?
- In our benchmarks, Ornith-1.5-9B-oQ8e scores 21.0/100 for coding. It runs at about 53.0 tok/s, so if you want more speed, Nex-N2.5-mini-IQ3_XXS is faster (~91.4 tok/s) and still scores well for coding (81.6/100).
- Is Ornith-1.5-9B-oQ8e good for agentic (tool-using) tasks?
- In our benchmarks, Ornith-1.5-9B-oQ8e scores 70.5/100 for agentic workflows. It runs at about 53.0 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 Ornith-1.5-9B-oQ8e for local inference?
- Across 2 community benchmark runs, Ornith-1.5-9B-oQ8e reaches up to 53.1 tok/s and averages 53.0 tok/s, with the fastest results on Apple M5 Max.
- How much memory does Ornith-1.5-9B-oQ8e need?
- The leanest observed configuration used about 11.5 GB of memory.
- Which tools have been used to run Ornith-1.5-9B-oQ8e?
- Benchmarks were submitted using oMLX. Results are community-contributed and updated as new runs arrive.