Model benchmarks

30cmtonyfaker/Qwen3.8-Flash-Next-REAP-288-MLX-Serve-4bit-MTP local LLM performance

As of September 2026, 30cmtonyfaker/Qwen3.8-Flash-Next-REAP-288-MLX-Serve-4bit-MTP runs at up to 81.4 tok/s for local inference (best of 3 community benchmark runs across 1 GPU).

vLLM
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Model size

Unknown

Peak speed

81.4 tok/s

Average speed

77.4 tok/s

Avg PP

922.8 tok/s

Min memory

n/a

Max context

262.144 tokens

Avg output / run

4.984 tokens

Avg runtime / run

1m 8s

Avg quality

54.0

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)
Overall51.254.057.6
Agent Workflow47.861.574.1
Code Generation0.07.620.5
Role Play & Narrative76.478.882.4
Research & Analysis64.568.273.2

Performance by hardware and tool

Every hardware/tool/quantization combination 30cmtonyfaker/Qwen3.8-Flash-Next-REAP-288-MLX-Serve-4bit-MTP has been benchmarked on, ranked by peak token generation speed. Last updated September 2026.

HardwareToolQuantBest tok/sAvg tok/sMemoryContextQualityRuns
Apple M5 MaxvLLM81.4 tok/s77.4 tok/sn/a262.144 tokens54.03

Benchmark runs

All 3 30cmtonyfaker/Qwen3.8-Flash-Next-REAP-288-MLX-Serve-4bit-MTP runs submitted so far — expand one for its hardware, quality breakdown and per-scenario detail.

Frequently asked questions

Is 30cmtonyfaker/Qwen3.8-Flash-Next-REAP-288-MLX-Serve-4bit-MTP good for coding?
In our benchmarks, 30cmtonyfaker/Qwen3.8-Flash-Next-REAP-288-MLX-Serve-4bit-MTP scores 7.6/100 for coding. It runs at about 77.4 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 30cmtonyfaker/Qwen3.8-Flash-Next-REAP-288-MLX-Serve-4bit-MTP good for agentic (tool-using) tasks?
In our benchmarks, 30cmtonyfaker/Qwen3.8-Flash-Next-REAP-288-MLX-Serve-4bit-MTP scores 61.5/100 for agentic workflows. It runs at about 77.4 tok/s, so if you want more speed, Ornith-1.5-35B-A3B-BigBang-oQ8e-mtp is faster (~102.7 tok/s) and still scores well for agentic workflows (91.1/100).
How fast is 30cmtonyfaker/Qwen3.8-Flash-Next-REAP-288-MLX-Serve-4bit-MTP for local inference?
Across 3 community benchmark runs, 30cmtonyfaker/Qwen3.8-Flash-Next-REAP-288-MLX-Serve-4bit-MTP reaches up to 81.4 tok/s and averages 77.4 tok/s, with the fastest results on Apple M5 Max.
How much memory does 30cmtonyfaker/Qwen3.8-Flash-Next-REAP-288-MLX-Serve-4bit-MTP need?
The leanest observed configuration used about n/a of memory.
Which tools have been used to run 30cmtonyfaker/Qwen3.8-Flash-Next-REAP-288-MLX-Serve-4bit-MTP?
Benchmarks were submitted using vLLM. Results are community-contributed and updated as new runs arrive.