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Qwen3.5 model leads local AI coding benchmarks on M4 Pro, outperforming others significantly

By PulseAugur Editorial · [1 sources] ·

A recent benchmark test on a MacBook Pro with an M4 Pro chip revealed significant performance differences among local coding AI models. The Qwen3.5:35b-a3b-coding-nvfp4 model achieved an impressive 64.10 tokens per second, making it approximately 6.7 times faster than the Qwen3.6:27b model, which managed only 9.56 tokens per second. This speed difference is crucial for practical AI coding agent workflows, where multiple generations and tool calls are common, impacting overall productivity. AI

IMPACT Faster local models can significantly improve the productivity and responsiveness of AI coding agents.

RANK_REASON Benchmark results of local AI models. [lever_c_demoted from research: ic=1 ai=1.0]

Read on Medium — AI coding tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Qwen3.5 model leads local AI coding benchmarks on M4 Pro, outperforming others significantly

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0 / 100
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Newsworthiness bucket
Tool
Benchmark results of local AI models. [lever_c_demoted from research: ic=1 ai=1.0]
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Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
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product, infra
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High
Clearly on-topic for AI-industry coverage.
Story freshness
87 days old
Aged out of breaking-news scoring windows; ranking reflects the durable signal from the full source set.

Full methodology in our editorial standards.

COVERAGE [1]

  1. Medium — AI coding tag TIER_1 English(EN) · Ashwani Garg ·

    I Tested 4 Local Coding Models on My M4 Pro. One Was 6.7× Faster

    <div class="medium-feed-item"><p class="medium-feed-image"><a href="https://gargashwani.medium.com/i-tested-4-local-coding-models-on-my-m4-pro-one-was-6-7-faster-5257046c2707?source=rss------ai_coding-5"><img src="https://cdn-images-1.medium.com/max/2600/1*AvIIqjrWDQ0MB-e-_ycb4w.…

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