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Qwen3-Coder-Next quants trade blows on Mac

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Qwen3-Coder-Next quants trade blows on Mac
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// 55d agoBENCHMARK RESULT

Qwen3-Coder-Next quants trade blows on Mac

A 128-question LiveBench coding run on an M1 Max 64GB found Qwen3-Coder-Next’s bf16 API version slightly ahead, but GGUF and MLX quants clustered tightly behind it. The result suggests backend choice matters less for raw quality than for memory footprint, tooling, and runtime stability.

// ANALYSIS

The big takeaway is that Qwen3-Coder-Next looks pretty quantization-tolerant on coding tasks: the local 3-bit and 4-bit runs stayed close enough to bf16 that one-off benchmark noise could easily reshuffle the order.

  • bf16 led at 65.0% average pass rate, but the best local quants landed within a few points, which is a small gap for a single-run eval
  • MLX 4-bit slightly outperformed the GGUFs on this run, but the spread is narrow enough that it’s better read as “rough parity” than a decisive win
  • The author’s claim that MLX is not meaningfully faster than GGUFs is supported by the numbers here, especially once you factor in the reported oMLX throughput bug
  • For Mac users, this points to a practical decision tree: use whichever runtime is most stable and easiest to serve, because quality differences at 3-4 bits appear modest
  • The benchmark is still anecdotal, so it’s more useful as a sanity check than a final verdict on MLX vs llama.cpp
// TAGS
qwen3-coder-nextbenchmarkai-codingllminferenceopen-sourceself-hosted

DISCOVERED

55d ago

2026-04-02

PUBLISHED

55d ago

2026-04-02

RELEVANCE

9/ 10

AUTHOR

Ayumu_Kasuga