Is Unsloth-Ornith-1.5-35B-A3B-UD-IQ3_XXS good for coding?

In our benchmarks, Unsloth-Ornith-1.5-35B-A3B-UD-IQ3_XXS scores 76.7/100 for coding. It runs at about 88.4 tok/s, so if you want more speed, Ornith-1.5-35B-A3B.APEX-I-NanoPlus is faster (~110.5 tok/s) and still scores well for coding (81.1/100).

Is Unsloth-Ornith-1.5-35B-A3B-UD-IQ3_XXS good for agentic (tool-using) tasks?

In our benchmarks, Unsloth-Ornith-1.5-35B-A3B-UD-IQ3_XXS scores 75.0/100 for agentic workflows. It runs at about 88.4 tok/s, so if you want more speed, qwen3.8-flash-next-iq3_s is faster (~111.3 tok/s) and still scores well for agentic workflows (90.6/100).

How fast is Unsloth-Ornith-1.5-35B-A3B-UD-IQ3_XXS for local inference?

Across 7 community benchmark runs, Unsloth-Ornith-1.5-35B-A3B-UD-IQ3_XXS reaches up to 89.7 tok/s and averages 88.4 tok/s, with the fastest results on NVIDIA GeForce RTX 5060.

How much memory does Unsloth-Ornith-1.5-35B-A3B-UD-IQ3_XXS need?

The leanest observed configuration used about 18.9 GB of memory.

Which tools have been used to run Unsloth-Ornith-1.5-35B-A3B-UD-IQ3_XXS?

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

Model benchmarks

Unsloth-Ornith-1.5-35B-A3B-UD-IQ3_XXS local LLM performance

As of September 2026, Unsloth-Ornith-1.5-35B-A3B-UD-IQ3_XXS runs at up to 89.7 tok/s for local inference (best of 7 community benchmark runs across 1 GPU).

llama.cpp

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Model size

35B

Peak speed

89.7 tok/s

Average speed

88.4 tok/s

Avg PP

1108.4 tok/s

Min memory

18.9 GB

Max context

262,144 tokens

Avg output / run

21,141 tokens

Avg runtime / run

4m 7s

Avg quality

80.7

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 7 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	72.7	80.7	85.9
Agent Workflow	37.3	75.0	87.4
Code Generation	64.9	76.7	85.7
Role Play & Narrative	84.3	88.6	93.2
Research & Analysis	78.8	82.6	88.0

Performance by hardware and tool

Every hardware/tool/quantization combination Unsloth-Ornith-1.5-35B-A3B-UD-IQ3_XXS 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	—	89.7 tok/s	88.4 tok/s	18.9 GB	262,144 tokens	80.7	7

Benchmark runs

All 7 Unsloth-Ornith-1.5-35B-A3B-UD-IQ3_XXS runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.

Open run page →

Frequently asked questions

Is Unsloth-Ornith-1.5-35B-A3B-UD-IQ3_XXS good for coding?: In our benchmarks, Unsloth-Ornith-1.5-35B-A3B-UD-IQ3_XXS scores 76.7/100 for coding. It runs at about 88.4 tok/s, so if you want more speed, Ornith-1.5-35B-A3B.APEX-I-NanoPlus is faster (~110.5 tok/s) and still scores well for coding (81.1/100).
Is Unsloth-Ornith-1.5-35B-A3B-UD-IQ3_XXS good for agentic (tool-using) tasks?: In our benchmarks, Unsloth-Ornith-1.5-35B-A3B-UD-IQ3_XXS scores 75.0/100 for agentic workflows. It runs at about 88.4 tok/s, so if you want more speed, qwen3.8-flash-next-iq3_s is faster (~111.3 tok/s) and still scores well for agentic workflows (90.6/100).
How fast is Unsloth-Ornith-1.5-35B-A3B-UD-IQ3_XXS for local inference?: Across 7 community benchmark runs, Unsloth-Ornith-1.5-35B-A3B-UD-IQ3_XXS reaches up to 89.7 tok/s and averages 88.4 tok/s, with the fastest results on NVIDIA GeForce RTX 5060.
How much memory does Unsloth-Ornith-1.5-35B-A3B-UD-IQ3_XXS need?: The leanest observed configuration used about 18.9 GB of memory.
Which tools have been used to run Unsloth-Ornith-1.5-35B-A3B-UD-IQ3_XXS?: Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.