Release2d ago
OpenAI's Tibo Says Dots Will Expand Its Model Family to Include GPT-6.1 Terra for Speed and Wider Reach
At 15:50 UTC on Nov 2, Tibo (@thsottiaux), whose X bio reads "Codex & ChatGPT @OpenAI", posted that OpenAI is working on expanding the family of frontier models that power dots, including GPT-6 Astra and GPT-6.1 Terra, with others to come. He said Terra brings speed and "a nice personality upgrade" and will help bring dots to more people. Dots are the always-on agents in ChatGPT with their own cloud computer, launched on GPT-6 Astra. This is a first-hand post by an OpenAI employee, not a formal company announcement; no timing or plan details have been published.
Benchmark13d ago
FrontierCS 2 benchmark: agents must rebuild a paper's deleted contribution in its own repo and beat the authors' code; Claude Opus 5.5 leads at 58%, 16 tasks unsolved
Teams from UC Berkeley, Princeton and others released FrontierCS 2 (arXiv 2610.29932): 48 tasks across 13 CS domains, each built by deleting a paper's contribution from the authors' released code. An agent has 5 hours to write it back and passes only if it beats the original on every metric and every hidden workload. Of 12 agents, Claude Opus 5.5 in Claude Code leads with a 58% pass rate, every other agent passes fewer than half, and 16 tasks have no passing run. On Oct 26 maintainer Wenhao Chai said a trace audit showed the Pi harness ends runs on refusals; rerun in Antigravity, Gemini 4 Argon now beats GPT-6 Astra and sits right behind Opus 5.5.
Benchmark13d ago
Artificial Analysis Releases HealthBench & MLCR-AA: Exposing Severe Verbosity Bias in Medical AI Rankings
Independent AI evaluation platform Artificial Analysis officially released HealthBench Professional alongside the length-normalized MLCR-AA index (@ArtificialAnlys). The benchmark revealed a pervasive industry blindspot: LLM-as-a-Judge evaluations suffer from acute 'verbosity bias', disproportionately rewarding longer generations regardless of medical conciseness. In raw HealthBench scoring where Anthropic outputs were 4–6x longer, Claude Opus 5.5 led at 71.4%. However, once length bias was scientifically normalized via MLCR-AA, GPT-6 Astra (max) tied Claude Sonnet 5.5 for #1, while Claude Opus 5.5 plummeted from #1 down to #6, setting a new rigorous standard for medical model evaluation.
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