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rank score age size name 1 62.0 8 - Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) 2 59.1 55 - GPT-5.5 (xhigh) 3 58.5 55 - GPT-5.5 (high) 4 57.2 104 - GPT-5.4 (…

score age size name 62.0 8 - Claude Fable 5 (Adaptive Reasoning, Max Effort, Opus 4.8 Fallback) 59.1 55 - GPT-5.5 (xhigh) 58.5 55 - GPT-5.5 (high) 57.2 104 - GPT-5.4 (xhigh) 56.7 2…

I had similar doubts. I think expectations differ because the workload differs. For small scripts, glue code, or simple CRUD changes, smaller models such as Qwen3.6-27B can work wo…

I'm not sure I would put too much weight on DeepSWE as a benchmark, given that GPT-5.4-mini ended up close to Opus 4.6 there.

My usual workflow is GPT-5.5 for planning, DeepSeek V4 Flash for milestones implementation, then GPT-5.5 again for review. It has worked pretty well so far.

I used to collect old hardware and try to install NetBSD/OpenBSD on them. For me, a lot of the fun was the "challenge accepted" aspect. Getting them to boot and work on some weird …