Model benchmarks

Qwen3.8-Flash-Next-oQ4e-mtp-BF16PLE-v1 local LLM performance

As of September 2026, Qwen3.8-Flash-Next-oQ4e-mtp-BF16PLE-v1 runs at up to 56.2 tok/s for local inference (best of 7 community benchmark runs across 1 GPU).

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Model size

Unknown

Peak speed

56.2 tok/s

Average speed

52.0 tok/s

Avg PP

378.2 tok/s

Min memory

78.7 GB

Max context

131.072 tokens

Avg output / run

60.767 tokens

Avg runtime / run

19m 20s

Avg quality

81.3

Benchmark runs

7

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 7 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)
Overall69.281.386.4
Agent Workflow26.677.592.4
Code Generation55.266.173.2
Role Play & Narrative87.291.594.5
Research & Analysis88.490.092.0

Performance by hardware and tool

Every hardware/tool/quantization combination Qwen3.8-Flash-Next-oQ4e-mtp-BF16PLE-v1 has been benchmarked on, ranked by peak token generation speed. Last updated September 2026.

HardwareToolQuantBest tok/sAvg tok/sMemoryContextQualityRuns
Apple M4 MaxoMLX56.2 tok/s52.0 tok/s78.7 GB131.072 tokens81.37

Benchmark runs

All 7 Qwen3.8-Flash-Next-oQ4e-mtp-BF16PLE-v1 runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.

Frequently asked questions

Is Qwen3.8-Flash-Next-oQ4e-mtp-BF16PLE-v1 good for coding?
In our benchmarks, Qwen3.8-Flash-Next-oQ4e-mtp-BF16PLE-v1 scores 66.1/100 for coding. It runs at about 52.0 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-oQ4e-mtp-BF16PLE-v1 good for agentic (tool-using) tasks?
In our benchmarks, Qwen3.8-Flash-Next-oQ4e-mtp-BF16PLE-v1 scores 77.5/100 for agentic workflows. It runs at about 52.0 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-oQ4e-mtp-BF16PLE-v1 for local inference?
Across 7 community benchmark runs, Qwen3.8-Flash-Next-oQ4e-mtp-BF16PLE-v1 reaches up to 56.2 tok/s and averages 52.0 tok/s, with the fastest results on Apple M4 Max.
How much memory does Qwen3.8-Flash-Next-oQ4e-mtp-BF16PLE-v1 need?
The leanest observed configuration used about 78.7 GB of memory.
Which tools have been used to run Qwen3.8-Flash-Next-oQ4e-mtp-BF16PLE-v1?
Benchmarks were submitted using oMLX. Results are community-contributed and updated as new runs arrive.