Is Qwen3.8-27B-oQ4e-mtp good for coding?

In our benchmarks, Qwen3.8-27B-oQ4e-mtp scores 76.2/100 for coding. It runs at about 44.5 tok/s, so if you want more speed, Nex-N2.5-mini-IQ3_XXS is faster (~80.3 tok/s) and still scores well for coding (84.5/100).

Is Qwen3.8-27B-oQ4e-mtp good for agentic (tool-using) tasks?

In our benchmarks, Qwen3.8-27B-oQ4e-mtp scores 81.9/100 for agentic workflows. It runs at about 44.5 tok/s, so if you want more speed, Nex-N2.5-mini-APEX-Mini is faster (~88.2 tok/s) and still scores well for agentic workflows (91.3/100).

How fast is Qwen3.8-27B-oQ4e-mtp for local inference?

Across 106 community benchmark runs, Qwen3.8-27B-oQ4e-mtp reaches up to 60.4 tok/s and averages 44.5 tok/s, with the fastest results on Apple M5 Max.

How much memory does Qwen3.8-27B-oQ4e-mtp need?

The leanest observed configuration used about 16.4 GB of memory (quantizations tested: oQ4e).

Which tools have been used to run Qwen3.8-27B-oQ4e-mtp?

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

Model benchmarks

Qwen3.8-27B-oQ4e-mtp local LLM performance

As of October 2026, Qwen3.8-27B-oQ4e-mtp runs at up to 60.4 tok/s for local inference (best of 106 community benchmark runs across 2 GPUs).

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Model size

27B

Peak speed

60.4 tok/s

Average speed

44.5 tok/s

Avg PP

310.4 tok/s

Min memory

16.4 GB

Max context

262,144 tokens

Avg output / run

25,855 tokens

Avg runtime / run

10m 42s

Avg quality

83.3

Benchmark runs

106

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 106 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	77.4	83.3	87.3
Agent Workflow	67.9	81.9	91.0
Code Generation	66.7	76.2	85.9
Role Play & Narrative	78.6	89.3	95.5
Research & Analysis	79.8	85.6	89.2

Performance by hardware and tool

Every hardware/tool/quantization combination Qwen3.8-27B-oQ4e-mtp has been benchmarked on, ranked by peak token generation speed. Last updated October 2026.

Hardware	Tool	Quant	Best tok/s	Avg tok/s	Memory	Context	Quality	Runs
Apple M5 Max	oMLX	oQ4e	60.4 tok/s	39.3 tok/s	16.4 GB	262,144 tokens	82.4	10
Apple M5 Max	oMLX	—	55.1 tok/s	45.3 tok/s	17.0 GB	262,144 tokens	83.5	26
Apple M4 Max	oMLX	—	47.2 tok/s	44.9 tok/s	30.3 GB	262,144 tokens	83.3	40
Apple M4 Max	oMLX	oQ4e	46.5 tok/s	45.0 tok/s	22.3 GB	262,144 tokens	83.4	30

Benchmark runs

All 106 Qwen3.8-27B-oQ4e-mtp runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.

Open run page →

Frequently asked questions

Is Qwen3.8-27B-oQ4e-mtp good for coding?: In our benchmarks, Qwen3.8-27B-oQ4e-mtp scores 76.2/100 for coding. It runs at about 44.5 tok/s, so if you want more speed, Nex-N2.5-mini-IQ3_XXS is faster (~80.3 tok/s) and still scores well for coding (84.5/100).
Is Qwen3.8-27B-oQ4e-mtp good for agentic (tool-using) tasks?: In our benchmarks, Qwen3.8-27B-oQ4e-mtp scores 81.9/100 for agentic workflows. It runs at about 44.5 tok/s, so if you want more speed, Nex-N2.5-mini-APEX-Mini is faster (~88.2 tok/s) and still scores well for agentic workflows (91.3/100).
How fast is Qwen3.8-27B-oQ4e-mtp for local inference?: Across 106 community benchmark runs, Qwen3.8-27B-oQ4e-mtp reaches up to 60.4 tok/s and averages 44.5 tok/s, with the fastest results on Apple M5 Max.
How much memory does Qwen3.8-27B-oQ4e-mtp need?: The leanest observed configuration used about 16.4 GB of memory (quantizations tested: oQ4e).
Which tools have been used to run Qwen3.8-27B-oQ4e-mtp?: Benchmarks were submitted using oMLX. Results are community-contributed and updated as new runs arrive.