Fabian G. Williams aka Fabs

Fabian G. Williams

Principal Product Manager, Microsoft Subscribe to my YouTube.

I Swapped My Local Coding Model Overnight From a Hotel. The Agent Graded the Upgrade Itself.

Local models are how I run my community work, my volunteer projects, my side hustles, and my musings, for two reasons: cost and keeping client data away from the labs. A new version dropped, so I upgraded it overnight from a hotel, additively, without touching the old one. Then I handed the new model the reviews and let my OpenCode agent test its own upgrade. It stood up a throwaway server, probed itself, and found three config gaps quietly throttling it. Here is the journey, in tables.

Fabian Williams

8-Minute Read

Activity Monitor showing the M3 Max GPU pinned at 92 percent while an OpenCode agent runs probe requests against a throwaway Qwen3.8 test server on port 8082

Local models are how I run my community work, my volunteer projects, my side hustles, and my musings. Two reasons, both simple:

Qwen 3.6 vs gpt-oss:120b on M3 Max: I Ran a Harder Test, the 8× Speed Gap Surprised Me

I published a Qwen 3.6 vs gpt-oss migration story, then ran an un-gameable eval against both on the same M3 Max. The receipts changed the speed narrative — gpt-oss:120b ran 8 to 11 times faster than qwen3.6:27b at parity reasoning quality. Here is the methodology and the data.

Fabian Williams

11-Minute Read

Horizontal bar chart showing gpt-oss:120b at 137 seconds and qwen3.6:27b at 1593 seconds on the same Round 2 reasoning tasks, with an 11.6× slower callout

I published a post last week about replacing gpt-oss:120b with Qwen 3.6 on my MacBook Pro M3 Max. The numbers in that post were real, but one set of tests was structurally gameable — 38 of 40 baseline images were the same class, so an “always-say-A” stub also scored 95 percent. I went back, designed three un-gameable reasoning tasks, and ran them against both local models on identical hardware. gpt-oss:120b finished the three tasks in 137 seconds. qwen3.6:27b-q8_0 took 1593 seconds —…

Replacing gpt-oss:120b With Qwen3.6 on a MacBook Pro: A Two-Day Local Model Benchmark

Two days benchmarking three Qwen3.6 variants against gpt-oss:120b on an M3 Max. A 21 GB coding-tuned model ran an OpenClaw-shaped research-brief workload 10x faster than gpt-oss — fast enough to seriously consider moving the work off SaaS frontier APIs. Plus the silent-hallucination trap I almost shipped through.

Fabian Williams

14-Minute Read

Bar chart comparing wall time of four local models on a structured-output benchmark

I spent two days benchmarking three Qwen3.6 variants against gpt-oss:120b on my MacBook Pro M3 Max. The shocking result: a 21 GB coding-tuned model ran an OpenClaw-shaped research-brief workload that I use for the non profit MACONA.org in 6 seconds — 10x faster than gpt-oss:120b on the same prompt. Fast enough that I now have reasonable confidence I could move this kind of work off the SaaS-hosted frontier models I have been paying for and onto local hardware on my dev machine. The deeper…

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