Is Qwen3.8-Flash-Next-oQ4e-mix6-mtp good for coding?

In our benchmarks, Qwen3.8-Flash-Next-oQ4e-mix6-mtp scores 74.0/100 for coding. It runs at about 72.9 tok/s, so if you want more speed, ornith-ai/Ornith-1.5-35B-A3B-GGUF is faster (~90.8 tok/s) and still scores well for coding (83.8/100).

Is Qwen3.8-Flash-Next-oQ4e-mix6-mtp good for agentic (tool-using) tasks?

In our benchmarks, Qwen3.8-Flash-Next-oQ4e-mix6-mtp scores 82.1/100 for agentic workflows. It runs at about 72.9 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-Flash-Next-oQ4e-mix6-mtp for local inference?

Across 10 community benchmark runs, Qwen3.8-Flash-Next-oQ4e-mix6-mtp reaches up to 77.8 tok/s and averages 72.9 tok/s, with the fastest results on Apple M4 Max.

How much memory does Qwen3.8-Flash-Next-oQ4e-mix6-mtp need?

The leanest observed configuration used about 77.5 GB of memory (quantizations tested: oQ4e).

Which tools have been used to run Qwen3.8-Flash-Next-oQ4e-mix6-mtp?

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

Model benchmarks

Qwen3.8-Flash-Next-oQ4e-mix6-mtp local LLM performance

As of October 2026, Qwen3.8-Flash-Next-oQ4e-mix6-mtp runs at up to 77.8 tok/s for local inference (best of 10 community benchmark runs across 1 GPU).

oMLXoQ4e

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Model size

Unknown

Peak speed

77.8 tok/s

Average speed

72.9 tok/s

Avg PP

4261.9 tok/s

Min memory

77.5 GB

Max context

65,536 tokens

Avg output / run

10,992 tokens

Avg runtime / run

2m 33s

Avg quality

81.9

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 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.

Task	P5 (low)	Avg	P95 (high)
Overall	80.0	81.9	84.6
Agent Workflow	77.0	82.1	87.6
Code Generation	65.8	74.0	79.9
Role Play & Narrative	80.0	87.4	92.8
Research & Analysis	79.4	84.2	88.8

Performance by hardware and tool

Every hardware/tool/quantization combination Qwen3.8-Flash-Next-oQ4e-mix6-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 M4 Max	oMLX	oQ4e	77.8 tok/s	72.9 tok/s	77.5 GB	65,536 tokens	81.9	10

Benchmark runs

All 10 Qwen3.8-Flash-Next-oQ4e-mix6-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-Flash-Next-oQ4e-mix6-mtp good for coding?: In our benchmarks, Qwen3.8-Flash-Next-oQ4e-mix6-mtp scores 74.0/100 for coding. It runs at about 72.9 tok/s, so if you want more speed, ornith-ai/Ornith-1.5-35B-A3B-GGUF is faster (~90.8 tok/s) and still scores well for coding (83.8/100).
Is Qwen3.8-Flash-Next-oQ4e-mix6-mtp good for agentic (tool-using) tasks?: In our benchmarks, Qwen3.8-Flash-Next-oQ4e-mix6-mtp scores 82.1/100 for agentic workflows. It runs at about 72.9 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-Flash-Next-oQ4e-mix6-mtp for local inference?: Across 10 community benchmark runs, Qwen3.8-Flash-Next-oQ4e-mix6-mtp reaches up to 77.8 tok/s and averages 72.9 tok/s, with the fastest results on Apple M4 Max.
How much memory does Qwen3.8-Flash-Next-oQ4e-mix6-mtp need?: The leanest observed configuration used about 77.5 GB of memory (quantizations tested: oQ4e).
Which tools have been used to run Qwen3.8-Flash-Next-oQ4e-mix6-mtp?: Benchmarks were submitted using oMLX. Results are community-contributed and updated as new runs arrive.