Model benchmarks
ornith-ai/Ornith-1.5-9B-GGUF local LLM performance
As of September 2026, ornith-ai/Ornith-1.5-9B-GGUF runs at up to 87.2 tok/s for local inference (best of 3 community benchmark runs across 1 GPU).
Model size
9B
Peak speed
87.2 tok/s
Average speed
66.4 tok/s
Avg PP
1344.8 tok/s
Min memory
11.9 GB
Max context
65,536 tokens
Avg output / run
72,597 tokens
Avg runtime / run
18m 31s
Avg quality
64.7
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 | 58.7 | 64.7 | 72.4 |
| Agent Workflow | 48.4 | 66.7 | 80.6 |
| Code Generation | 3.6 | 28.1 | 46.7 |
| Role Play & Narrative | 74.5 | 78.4 | 82.1 |
| Research & Analysis | 84.6 | 85.6 | 86.3 |
Performance by hardware and tool
Every hardware/tool/quantization combination ornith-ai/Ornith-1.5-9B-GGUF has been benchmarked on, ranked by peak token generation speed. Last updated September 2026.
| Hardware | Tool | Quant | Best tok/s | Avg tok/s | Memory | Context | Quality | Runs |
|---|---|---|---|---|---|---|---|---|
| NVIDIA GeForce RTX 4070 | Unsloth Studio | Q6_K | 87.2 tok/s | 66.4 tok/s | 11.9 GB | 65,536 tokens | 64.7 | 3 |
Benchmark runs
All 3 ornith-ai/Ornith-1.5-9B-GGUF runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.
Frequently asked questions
- Is ornith-ai/Ornith-1.5-9B-GGUF good for coding?
- In our benchmarks, ornith-ai/Ornith-1.5-9B-GGUF scores 28.1/100 for coding. It runs at about 66.4 tok/s, so if you want more speed, Tiel-Coder-35B-A3B-MLX-oQ4e is faster (~107.9 tok/s) and still scores well for coding (81.5/100).
- Is ornith-ai/Ornith-1.5-9B-GGUF good for agentic (tool-using) tasks?
- In our benchmarks, ornith-ai/Ornith-1.5-9B-GGUF scores 66.7/100 for agentic workflows. It runs at about 66.4 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-ai/Ornith-1.5-9B-GGUF for local inference?
- Across 3 community benchmark runs, ornith-ai/Ornith-1.5-9B-GGUF reaches up to 87.2 tok/s and averages 66.4 tok/s, with the fastest results on NVIDIA GeForce RTX 4070.
- How much memory does ornith-ai/Ornith-1.5-9B-GGUF need?
- The leanest observed configuration used about 11.9 GB of memory (quantizations tested: Q6_K).
- Which tools have been used to run ornith-ai/Ornith-1.5-9B-GGUF?
- Benchmarks were submitted using Unsloth Studio. Results are community-contributed and updated as new runs arrive.