Mystery model Ox Alpha scores 63% on full DeepSWE run, not the earlier 80%
daniel_mac8 · x · 2026-08-23
@davis7 completed a full DeepSWE benchmark run on the mysterious ox alpha model: it ended at 63%, not the 80% his earlier subset test suggested — which makes far more sense.
Hands-on impressions: much better "voice" than Claude or GPT, decent design, handles subagents and long complex work well, good code quality and instruction parsing. Quirks: sometimes leaves dead code around (less thorough than Sol), and despite decent TPS it doesn't feel fast — higher reasoning levels take very long to run, raising efficiency questions.
@davis7 still calls it a very good model; @dedene notes 63% is strong given Fable sits at 69%, predicting ox alpha will be very popular.
Related event: Ox Alpha scores ~63% on full DeepSWE; earlier 80% was subset artifact(6 posts)→
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