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OpenAI has published three results produced by its internal models, in theoretical computer science, mathematics, and physics, with proofs formalized in Lean. None have yet been validated by the community, and independent groups of researchers are tasked with reviewing them.
Available since October 26 in ChatGPT, Codex and the API, GPT-6.1 Terra costs $1 per million input tokens. Its performance gains have, for now, been measured only by OpenAI.
The new lab is betting on context length rather than size. Fern 0.1 is not yet available, and its own coding scores remain well below those of the best models.
Released on Hugging Face with its weights and a 512,000-token context, the model beats similarly sized rivals on most of the tests published by its developer, but not all of them.
The ARC Prize measured both scores itself: the gap comes from how the model keeps its reasoning from one request to the next.
Scored at 55 by Artificial Analysis, the model combines a top-tier ranking with aggressive pricing. Its weights are promised by November 4.
Google's new model has been open to developers and paying subscribers since October 13. Another variant is reportedly being tested internally, without official confirmation.
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