Model benchmarks
Ornith-1.5-9B-MLX-8bit local LLM performance
As of August 2026, Ornith-1.5-9B-MLX-8bit runs at up to 54.4 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).
Model size
9B
Peak speed
54.4 tok/s
Average speed
53.0 tok/s
Min memory
9.6 GB
Max context
262,144 tokens
Avg output / run
51,595 tokens
Avg runtime / run
21m 41s
Avg quality
63.5
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 | 62.2 | 63.5 | 64.9 |
| Agent Workflow | 71.7 | 72.9 | 74.1 |
| Code Generation | 2.4 | 24.5 | 46.5 |
| Role Play & Narrative | 58.0 | 72.8 | 87.7 |
| Research & Analysis | 83.2 | 84.0 | 84.8 |
Performance by hardware and tool
Every hardware/tool/quantization combination Ornith-1.5-9B-MLX-8bit 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 | — | 54.4 tok/s | 53.0 tok/s | 9.6 GB | 262,144 tokens | 63.5 | 2 |
Frequently asked questions
- Is Ornith-1.5-9B-MLX-8bit good for coding?
- In our benchmarks, Ornith-1.5-9B-MLX-8bit scores 24.5/100 for coding. It runs at about 53.0 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-1.5-9B-MLX-8bit good for agentic (tool-using) tasks?
- In our benchmarks, Ornith-1.5-9B-MLX-8bit scores 72.9/100 for agentic workflows. It runs at about 53.0 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-1.5-9B-MLX-8bit for local inference?
- Across 2 community benchmark runs, Ornith-1.5-9B-MLX-8bit reaches up to 54.4 tok/s and averages 53.0 tok/s, with the fastest results on Apple M5 Max.
- How much memory does Ornith-1.5-9B-MLX-8bit need?
- The leanest observed configuration used about 9.6 GB of memory.
- Which tools have been used to run Ornith-1.5-9B-MLX-8bit?
- Benchmarks were submitted using oMLX. Results are community-contributed and updated as new runs arrive.