Looping models too big a performance gain to ignore, but monitoring lags, says AI commentator
scaling01 · x · 2026-10-13
Responding to a question about whether Anthropic would ever ship looping models, @scaling01 argues that if Anthropic maintains its lead (as with the rumored Opus 5.5), there's no reason not to adopt looping once monitoring catches up — and that the performance gain is ultimately too large to leave on the table long-term. The exchange touches on the tension between a frontier inference paradigm and current safety/monitoring tooling.
More from Models
- Same model scores 24% vs 59% across harnesses, Chamath declares leaderboards worthless — eliano · 2026-10-13
- Meta unveils Personal Superintelligence Index, its Muse Wonder tops at 59.1% — ChrisGPT · 2026-10-13
- Cloudflare serves Clef with SGLang: sub-40ms latency on a single H200 — ying11231 · 2026-10-13
- Meta Muse hits 5M downloads in 22 days, nearly 3x faster than ChatGPT — aakashgupta · 2026-10-13
- Muse Wonder accused of benchmaxxing: costs $18 vs free SWE 2 and performs worse — lyraxana · 2026-10-13
- Writer ditches $200/mo Opus 5.5 for Gemini 4 over one reason: it writes well — iamtrask · 2026-10-13