Model benchmarks

allenai.OLMoE-1B-7B-0125-Instruct.Q5_K_M local LLM performance

As of October 2026, allenai.OLMoE-1B-7B-0125-Instruct.Q5_K_M runs at up to 188.7 tok/s for local inference (best of 10 community benchmark runs across 1 GPU).

llama.cppQ5_K_M
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Model size

7B

Peak speed

188.7 tok/s

Average speed

185.1 tok/s

Avg PP

1039.8 tok/s

Min memory

7.6 GB

Max context

32,768 tokens

Avg output / run

4,995 tokens

Avg runtime / run

30s

Avg quality

31.4

Benchmark runs

10

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 10 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)
Overall25.331.438.5
Agent Workflow18.640.564.1
Code Generation5.78.312.3
Role Play & Narrative39.553.562.2
Research & Analysis15.023.129.6

Performance by hardware and tool

Every hardware/tool/quantization combination allenai.OLMoE-1B-7B-0125-Instruct.Q5_K_M has been benchmarked on, ranked by peak token generation speed. Last updated October 2026.

HardwareToolQuantBest tok/sAvg tok/sMemoryContextQualityRuns
NVIDIA GeForce RTX 4060 Laptop GPUllama.cppQ5_K_M188.7 tok/s185.1 tok/s7.6 GB32,768 tokens31.410

Benchmark runs

All 10 allenai.OLMoE-1B-7B-0125-Instruct.Q5_K_M runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.

Frequently asked questions

How fast is allenai.OLMoE-1B-7B-0125-Instruct.Q5_K_M for local inference?
Across 10 community benchmark runs, allenai.OLMoE-1B-7B-0125-Instruct.Q5_K_M reaches up to 188.7 tok/s and averages 185.1 tok/s, with the fastest results on NVIDIA GeForce RTX 4060 Laptop GPU.
How much memory does allenai.OLMoE-1B-7B-0125-Instruct.Q5_K_M need?
The leanest observed configuration used about 7.6 GB of memory (quantizations tested: Q5_K_M).
Which tools have been used to run allenai.OLMoE-1B-7B-0125-Instruct.Q5_K_M?
Benchmarks were submitted using llama.cpp. Results are community-contributed and updated as new runs arrive.