Model benchmarks

Qwen3.8-Flash-Next-Dynamic-oQ4e-Q4GU-g64-BF16-PLE-MLX-mtp local LLM performance

As of September 2026, Qwen3.8-Flash-Next-Dynamic-oQ4e-Q4GU-g64-BF16-PLE-MLX-mtp runs at up to 49.9 tok/s for local inference (best of 3 community benchmark runs across 1 GPU).

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Model size

4B

Peak speed

49.9 tok/s

Average speed

48.7 tok/s

Avg prefill

372.4 tok/s

Min memory

81.8 GB

Max context

262,144 tokens

Avg output / run

28,961 tokens

Avg runtime / run

9m 56s

Avg quality

81.7

Benchmark runs

3

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 3 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)
Overall75.981.786.7
Agent Workflow82.986.291.5
Code Generation59.069.075.9
Role Play & Narrative77.985.193.0
Research & Analysis83.486.688.5

Performance by hardware and tool

Every hardware/tool/quantization combination Qwen3.8-Flash-Next-Dynamic-oQ4e-Q4GU-g64-BF16-PLE-MLX-mtp has been benchmarked on, ranked by peak token generation speed. Last updated September 2026.

HardwareToolQuantBest tok/sAvg tok/sMemoryContextQualityRuns
Apple M4 MaxoMLX49.9 tok/s48.7 tok/s81.8 GB262,144 tokens81.73

Frequently asked questions

Is Qwen3.8-Flash-Next-Dynamic-oQ4e-Q4GU-g64-BF16-PLE-MLX-mtp good for coding?
In our benchmarks, Qwen3.8-Flash-Next-Dynamic-oQ4e-Q4GU-g64-BF16-PLE-MLX-mtp scores 69.0/100 for coding. It runs at about 48.7 tok/s, so if you want more speed, unsloth/Qwen3.8-27B-GGUF:IQ3_S is faster (~104.3 tok/s) and still scores well for coding (83.0/100).
Is Qwen3.8-Flash-Next-Dynamic-oQ4e-Q4GU-g64-BF16-PLE-MLX-mtp good for agentic (tool-using) tasks?
In our benchmarks, Qwen3.8-Flash-Next-Dynamic-oQ4e-Q4GU-g64-BF16-PLE-MLX-mtp scores 86.3/100 for agentic workflows. It runs at about 48.7 tok/s, so if you want more speed, granite-4.2-8b-Q4_K_L is faster (~71.6 tok/s) and still scores well for agentic workflows (92.9/100).
How fast is Qwen3.8-Flash-Next-Dynamic-oQ4e-Q4GU-g64-BF16-PLE-MLX-mtp for local inference?
Across 3 community benchmark runs, Qwen3.8-Flash-Next-Dynamic-oQ4e-Q4GU-g64-BF16-PLE-MLX-mtp reaches up to 49.9 tok/s and averages 48.7 tok/s, with the fastest results on Apple M4 Max.
How much memory does Qwen3.8-Flash-Next-Dynamic-oQ4e-Q4GU-g64-BF16-PLE-MLX-mtp need?
The leanest observed configuration used about 81.8 GB of memory.
Which tools have been used to run Qwen3.8-Flash-Next-Dynamic-oQ4e-Q4GU-g64-BF16-PLE-MLX-mtp?
Benchmarks were submitted using oMLX. Results are community-contributed and updated as new runs arrive.