Model benchmarks

Ornith-1.5-35B-A3B-BigBang-oQ8e-mtp local LLM performance

As of August 2026, Ornith-1.5-35B-A3B-BigBang-oQ8e-mtp runs at up to 106.9 tok/s for local inference (best of 2 community benchmark runs across 1 GPU).

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Model size

35B

Peak speed

106.9 tok/s

Average speed

102.7 tok/s

Min memory

36.8 GB

Max context

262,144 tokens

Avg runtime / run

2m 42s

Avg quality

84.5

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.

TaskP5 (low)AvgP95 (high)
Overall81.884.587.2
Agent Workflow89.691.192.5
Code Generation63.170.978.7
Role Play & Narrative87.487.988.5
Research & Analysis87.187.988.8

Performance by hardware and tool

Every hardware/tool/quantization combination Ornith-1.5-35B-A3B-BigBang-oQ8e-mtp has been benchmarked on, ranked by peak token generation speed. Last updated August 2026.

HardwareToolQuantBest tok/sAvg tok/sMemoryContextQualityRuns
Apple M5 MaxoMLX—106.9 tok/s102.7 tok/s36.8 GB262,144 tokens84.52

Benchmark runs

All 2 Ornith-1.5-35B-A3B-BigBang-oQ8e-mtp runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.

Frequently asked questions

Is Ornith-1.5-35B-A3B-BigBang-oQ8e-mtp good for coding?
In our benchmarks, Ornith-1.5-35B-A3B-BigBang-oQ8e-mtp scores 70.9/100 for coding. It runs at about 102.7 tok/s, so if you want more speed, Qwen3.6-35B-A3B-Q4_K_XL is faster (~156.9 tok/s) and still scores well for coding (82.2/100).
Is Ornith-1.5-35B-A3B-BigBang-oQ8e-mtp good for agentic (tool-using) tasks?
In our benchmarks, Ornith-1.5-35B-A3B-BigBang-oQ8e-mtp scores 91.1/100 for agentic workflows. It runs at about 102.7 tok/s, so if you want more speed, Tiel-Coder-35B-A3B-Q4_K_S is faster (~162.4 tok/s) and still scores well for agentic workflows (87.8/100).
How fast is Ornith-1.5-35B-A3B-BigBang-oQ8e-mtp for local inference?
Across 2 community benchmark runs, Ornith-1.5-35B-A3B-BigBang-oQ8e-mtp reaches up to 106.9 tok/s and averages 102.7 tok/s, with the fastest results on Apple M5 Max.
How much memory does Ornith-1.5-35B-A3B-BigBang-oQ8e-mtp need?
The leanest observed configuration used about 36.8 GB of memory.
Which tools have been used to run Ornith-1.5-35B-A3B-BigBang-oQ8e-mtp?
Benchmarks were submitted using oMLX. Results are community-contributed and updated as new runs arrive.