The day's essential AI stories, from the labs, startups and researchers shaping it.
ITHome · AIFeaturedSame story · 4 outlets8787Why it matters: The original provides pricing, four tiers of thinking depth, and Terminal-Bench comparative data, allowing judgment on the trade-offs between cost and speed in daily coding scenarios.
The DecoderFeatured8585Google DeepMind releases AlphaProof Code, an AI-powered mathematical proof software that meets security specifications, and completes the verification work usually requiring several years on the Signal encryption protocol in just four weeks.
Claude · YouTubeFeaturedSame story · 4 outlets7575Anthropic releases Claude Fable 5.2, designed for the most challenging technical challenges, with improvements in coding, reasoning, and vision, suitable for the most ambitious open-ended technical work. The official recommendation is to use Opus 5.5 for most coding and knowledge tasks, and Fable 5.2 is now available in the Pro, Max, Team, and Enterprise packages.
How the accounts differ:TechCrunch states the input price of Fable is reduced to $8 per million tokens; others do not mention the price.
Why it matters: The official statement explains the positioning and applicable scenarios of Fable 5.2, and provides a choice suggestion between Opus 5.5, making it easier to decide which model to use.
ITHome · AIFeatured7272Meituan Longma has released the native multimodal model LongCat-2.5 for long-range intelligent agent tasks, with a total parameter count of 1.6 trillion, activating about 48 billion parameters per token, enhancing native visual understanding and intelligent agent programming capabilities based on LongCat-2.0.
Why it matters: The original text provides 1.6T parameters and activation scale, and explains how long-range reinforcement learning is used for complex codebase and project construction tasks.
Mistral AIFeatured8282Mistral releases open-weight version of its flagship trillion-parameter native multimodal model Mistral Large 4 (Le Chonk), which has been in public preview for three weeks.
Why it matters: The official provides data on the encoding, security, and inference efficiency of the trillion-parameter open-source model, as well as weight downloads and self-hosting paths.
Google DeepMindFeaturedSame story · 5 outlets8787Google DeepMind has opened Gemini 4 Carbon to developers, enterprises, scientists, and consumers, claiming it has reached cutting-edge levels in network security capabilities and long-range intelligent agent workflows.
Why it matters: The official provides the positioning division of roles between Carbon and Argon, multiple benchmark rankings, and cost comparisons per task to help determine when to use a heavier model.
The DecoderFeatured8585Why it matters: The article uses third-party indices and multiple benchmarks to present the specific extent to which the gap between open-source weight models and closed-source cutting-edge models has narrowed.
MarkTechPostFeatured8383Moonshot AI has released the first model of the K3.1 series, Kimi K3.1 Pro, which adopts a MoE architecture with a total parameter count of 2.8T and an activation parameter count of 104B, supporting a context length of 1M tokens. It has been launched on Kimi.ai, Kimi Work, Kimi Code, and Kimi API. The API pricing is $2 per million tokens for input and $10 for output, lower than K3's $3 and $15.
Why it matters: The original text lists the self-reported data of K3.1 Pro in terms of terminal encoding, scientific terminal tasks, and hallucination rate, and provides API pricing and open weight time.
The DecoderFeatured7474AI startup Recursive has released its first language model, Flint. During the development process, the AI system named Eureka Machine participated in proposing ideas, building, testing, and planning subsequent experiments.
Why it matters: Recursive publicly announces its first model developed with the assistance of an automated research system, allowing readers to observe how far AI-assisted R&D can go.
