Is ornith-1.5-35b-apex good for agentic (tool-using) tasks?

In our benchmarks, ornith-1.5-35b-apex scores 88.4/100 for agentic workflows. It runs at about 143.9 tok/s, so if you want more speed, swift-1.5-qwen3.8-flash-next-iq3_s is faster (~259.0 tok/s) and still scores well for agentic workflows (88.9/100).

How fast is ornith-1.5-35b-apex for local inference?

Across 3 community benchmark runs, ornith-1.5-35b-apex reaches up to 150.4 tok/s and averages 143.9 tok/s, with the fastest results on AMD Radeon AI PRO R9700.

Which tools have been used to run ornith-1.5-35b-apex?

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

Model benchmarks

ornith-1.5-35b-apex local LLM performance

As of November 2026, ornith-1.5-35b-apex runs at up to 150.4 tok/s for local inference (best of 3 community benchmark runs across 1 GPU).

llama.cpp

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Model size

35B

Peak speed

150.4 tok/s

Average speed

143.9 tok/s

Avg PP

1919.0 tok/s

Min memory

n/a

Max context

65,536 tokens

Avg output / run

49,477 tokens

Avg runtime / run

6m 6s

Avg quality

86.6

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 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	85.9	86.6	87.7
Agent Workflow	86.2	88.4	90.3
Code Generation	77.8	82.1	84.6
Role Play & Narrative	87.2	88.6	89.7
Research & Analysis	86.5	87.2	88.2

Performance by hardware and tool

Every hardware/tool/quantization combination ornith-1.5-35b-apex has been benchmarked on, ranked by peak token generation speed. Last updated November 2026.

Hardware	Tool	Quant	Best tok/s	Avg tok/s	Memory	Context	Quality	Runs
AMD Radeon AI PRO R9700	llama.cpp	—	150.4 tok/s	143.9 tok/s	n/a	65,536 tokens	86.6	3

Benchmark runs

All 3 ornith-1.5-35b-apex runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.

Open run page →

Frequently asked questions

Is ornith-1.5-35b-apex good for agentic (tool-using) tasks?: In our benchmarks, ornith-1.5-35b-apex scores 88.4/100 for agentic workflows. It runs at about 143.9 tok/s, so if you want more speed, swift-1.5-qwen3.8-flash-next-iq3_s is faster (~259.0 tok/s) and still scores well for agentic workflows (88.9/100).
How fast is ornith-1.5-35b-apex for local inference?: Across 3 community benchmark runs, ornith-1.5-35b-apex reaches up to 150.4 tok/s and averages 143.9 tok/s, with the fastest results on AMD Radeon AI PRO R9700.
Which tools have been used to run ornith-1.5-35b-apex?: Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.