Daily AI Briefing
The 6 top stories of the 120 AIBriefs curated that day.
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Kimi K3.1 Pro is a 3T-class MoE with 2.8T total / 104B active parameters and a 1M-token context, scoring 55 on the Artificial Analysis Intelligence Index — 4th overall and 11 points above Kimi K3. Weights aren't out yet; Moonshot promises full release by Nov 4, 2026, with API pricing at $2/M input and $10/M output.
The 65B dense model, pretrained on 12T tokens with up to 1M context, scored 80.52 on Terminal-Bench 2.1 — topping US open-weight rivals with 501B to 975B total parameters. Ricursive says full R&D cost was $32M, one-tenth the prior open-weight agentic coding leader.
The 770-billion-parameter flagship adds visual understanding and computer use, trained on apps like Blender and CAD. API pricing holds at $0.834/M input and $2.501/M output, with 50% off Tencent Cloud TokenHub through December 31.
OpenAI announced it will acquire Pierre Computer Company, whose open-source developer tools and Code Storage already power parts of Codex. Pierre's team will work on new Git workflows for Codex and developer tools.
OpenAI built an autonomous pipeline that found, validated, and generated patches for 948 local privilege-escalation vulnerabilities in the Linux kernel. The post frames the work as cutting down the number of paths to root.
M3.1 Flash is a 428B-parameter MoE with ~23B active and a 1M-token context, priced at $0.15 per 1M input tokens. MiniMax claims 70% lower agent costs and leads its Automation-Bench v1.0.6 at 62.2, but scores 38.1 on Terminal Bench 4.0 versus 51.8 for Opus 5.
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