The AI Wire ●

Moonshot AI released Kimi K3.1 Pro on Friday, a post-trained version of Kimi K3 with a 1 million-token context window, live now on Kimi.ai, the Kimi apps, Kimi Work, Kimi Code and the Kimi API. Moonshot calls it its most capable 3T-class open-weight model to date: 2.8 trillion total parameters with 104 billion active per token, text and image input, priced at $2 per million input tokens and $10 per million output — a third below K3 — with a Highspeed variant running two to three times faster at double the price.

Artificial Analysis scores it 55 on its Intelligence Index, fourth overall and an 11-point jump over K3, behind only Claude Opus 5.5, Claude Sonnet 5.5 and Muse Wonder Full. In Moonshot's own table it scores 65.7% on Terminal-Bench 4.0 against 66.4% for Opus 5.5, though almost every coding score was run inside Anthropic's Claude Code harness and the figures are not independently checked.

The full weights are promised by November 4; if they land as promised, K3.1 Pro would become the highest-scoring open-weights model on the Index. Moonshot also says it deliberately removed hacking-related data from training ahead of the open-weight release.

Reuters filled in the cyber curb on October 24: Moonshot said it removed cyber-related data not just from the training corpus but from the reinforcement-learning environments too, while keeping general coding skills. 'We aim not to release open weights that would extend the absolute frontier of cyber capability,' the company said; on its internal vulnerability-research test the final model scored 81.0%, against 90.5% for a checkpoint without the change (vendor-reported). The restraint lands a week after China proposed export controls that would ban exports of AI-driven malware-generation technology.

Update, November 4: the weights are out, two days ahead of the promise. Moonshot published the full model on Hugging Face on November 2 as moonshotai/Kimi-K3.1-Pro — 96 files, about 1.56 TB, not gated — under the Kimi K3.1-Pro License, word for word the K3 terms: free use, but a model-as-a-service business above $20 million in revenue over 12 months needs a separate agreement with Moonshot, and products above 100 million monthly users or $20 million in monthly revenue must display the model's name. Artificial Analysis was still listing the model as proprietary on November 4, two days after the upload.

Bloomberg reports that Harvey, the legal AI company valued at roughly $15.6 billion, has moved its flagship off closed frontier models. The driver is arithmetic: gross margins collapsed from about 50% to minus 50% by June as customer token usage jumped twentyfold under OpenAI and Anthropic's usage-based enterprise pricing.

In August Harvey launched Tenet, its first in-house model, post-trained on Moonshot's open-weight Kimi K3 (a 2.8-trillion-parameter base released in July) in work the company did with Fireworks AI. Margins turned positive again after the migration. Former AI czar David Sacks publicly backed the move, saying Harvey built 'world-class specialized models' at a fraction of frontier-model cost.

Bloomberg names Abridge, Decagon and Ramp as pursuing similar open-weight pivots, backed by Sequoia and General Catalyst — the first serious wave of enterprise AI companies leaving closed-model dependence, driven by unit economics rather than capability.