Is Ornith-1.5-9B-Q6_K good for coding?

In our benchmarks, Ornith-1.5-9B-Q6_K scores 64.2/100 for coding. It runs at about 51.6 tok/s, so if you want more speed, local-qwen is faster (~60.2 tok/s) and still scores well for coding (84.8/100).

Is Ornith-1.5-9B-Q6_K good for agentic (tool-using) tasks?

In our benchmarks, Ornith-1.5-9B-Q6_K scores 54.5/100 for agentic workflows. It runs at about 51.6 tok/s, so if you want more speed, granite-4.2-8b-Q4_K_L is faster (~71.6 tok/s) and still scores well for agentic workflows (92.9/100).

How fast is Ornith-1.5-9B-Q6_K for local inference?

Across 6 community benchmark runs, Ornith-1.5-9B-Q6_K reaches up to 74.4 tok/s and averages 51.6 tok/s, with the fastest results on NVIDIA GeForce RTX 5060.

Which tools have been used to run Ornith-1.5-9B-Q6_K?

Benchmarks were submitted using LM Studio, llama.cpp. Results are community-contributed and updated as new runs arrive.

Model benchmarks

Ornith-1.5-9B-Q6_K local LLM performance

As of September 2026, Ornith-1.5-9B-Q6_K runs at up to 74.4 tok/s for local inference (best of 6 community benchmark runs across 2 GPUs).

LM Studiollama.cppQ6_K

ShareReddit X

Model size

Peak speed

74.4 tok/s

Average speed

51.6 tok/s

Avg PP

1165.6 tok/s

Min memory

n/a

Max context

262,144 tokens

Avg output / run

28,687 tokens

Avg runtime / run

9m 37s

Avg quality

71.8

Benchmark runs

GPUs tested

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 6 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	63.0	71.8	81.0
Agent Workflow	24.8	54.5	83.8
Code Generation	48.8	64.2	75.2
Role Play & Narrative	76.9	83.5	88.3
Research & Analysis	80.8	84.9	88.3

Performance by hardware and tool

Every hardware/tool/quantization combination Ornith-1.5-9B-Q6_K 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 5060	llama.cpp	Q6_K	74.4 tok/s	57.6 tok/s	n/a	262,144 tokens	73.4	4
AMD Radeon RX 7600 XT	LM Studio	Q6_K	39.8 tok/s	39.5 tok/s	n/a	65,536 tokens	68.5	2

Benchmark runs

All 6 Ornith-1.5-9B-Q6_K runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.

Open run page →

Frequently asked questions

Is Ornith-1.5-9B-Q6_K good for coding?: In our benchmarks, Ornith-1.5-9B-Q6_K scores 64.2/100 for coding. It runs at about 51.6 tok/s, so if you want more speed, local-qwen is faster (~60.2 tok/s) and still scores well for coding (84.8/100).
Is Ornith-1.5-9B-Q6_K good for agentic (tool-using) tasks?: In our benchmarks, Ornith-1.5-9B-Q6_K scores 54.5/100 for agentic workflows. It runs at about 51.6 tok/s, so if you want more speed, granite-4.2-8b-Q4_K_L is faster (~71.6 tok/s) and still scores well for agentic workflows (92.9/100).
How fast is Ornith-1.5-9B-Q6_K for local inference?: Across 6 community benchmark runs, Ornith-1.5-9B-Q6_K reaches up to 74.4 tok/s and averages 51.6 tok/s, with the fastest results on NVIDIA GeForce RTX 5060.
Which tools have been used to run Ornith-1.5-9B-Q6_K?: Benchmarks were submitted using LM Studio, llama.cpp. Results are community-contributed and updated as new runs arrive.