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About 3 min read

Meta and DeepMind debut new models on the same day, updating open source and complex reasoning

The AI model space is exceptionally busy today. Meta is returning to the battlefield with an 816B open-source large model, DeepMind is rolling out Gemini 4 Argon globally—capable of even beating Minecraft—and Anthropic has posted $16.8 billion in quarterly revenue while workplace assistants quietly integrate into popular communication software.

Picked from 311 AIHOT stories, 1 podcast episode.

  • Products2
  • Tips1
  • Models3
  • Research1
  • Industry2

Today's highlights

  1. Meta open-sources 816B-parameter multimodal model Muse Spark Open
  2. DeepMind reasoning model Gemini 4 Argon officially available globally
  3. Anthropic Q3 revenue hits $16.8 billion, but quarter-over-quarter growth slows

01Products2 items

  1. Anthropic launches free, open-source code vulnerability scanner

    Anthropic has released a free, open-source AI scanner designed to automatically detect vulnerabilities in open-source software. The tool periodically scans code repositories, explains potential risks, and provides code fix patches, with an official expected accuracy rate of over 90%. Open-source project maintainers can apply to use it via GitHub.

    Why it matters Maintainers of open-source projects can get automated code security checks and patch recommendations for free.

    Read original· the-decoder.com(opens in a new tab)
  2. WeChat Work version 5.0.12 builds in WorkBuddy assistant

    WeChat Work and WorkBuddy have released the 5.0.12 update. After upgrading, users can chat directly with WorkBuddy in the chat interface. Within permitted boundaries, the assistant can read chat messages, collaborative documents, and meeting schedules, directly invoke workbench applications to process tasks, and feed execution results back into the chat window.

    Why it matters Users can have AI assist with document handling, meetings, and approval flows without leaving the chat app.

    Read original· ithome.com(opens in a new tab)

02Tips1 item

  1. Evaluation shows personal agent daily task delegation success rate is only 33%

    Researchers tested four personal agents—Google Muse, Grok Bot, OpenAI Dots, and Manus Cue—and found that only 33% successfully and stably delegated tasks across 12 daily platforms. The tests noted that cloud-based execution still struggles to detach from local environments, and tools equipped with native machine control capabilities showed more stable performance during actual interactions.

    Why it matters When wanting AI to take over computer operations, keep this success rate expectation in mind and prioritize tools capable of controlling the local machine.

    Read original· mp.weixin.qq.com(opens in a new tab)

03Models3 items

  1. Meta releases open-source model Muse Spark Open

    Meta has released the open-weight model Muse Spark Open, featuring 816 billion total parameters and 42 billion active parameters. The model supports a context window of up to 1 million tokens and natively supports text, image, video, and audio input. Officials describe it as a high-performance US open-weight model, benchmarked against Qwen, GLM, and Kimi.

    Why it matters When deploying locally or developing, you can use a large-parameter open-source base model that supports ultra-long text and multimodality.

    Read original· the-decoder.com(opens in a new tab)
  2. Google DeepMind announces Gemini 4 Argon available globally

    Google DeepMind has announced that the general-purpose model Gemini 4 Argon is officially available worldwide. The company states that the model is designed specifically to solve end-to-end, high-difficulty problems, boasting cutting-edge processing capabilities in complex coding, enterprise workflow orchestration, and cybersecurity tasks.

    Why it matters A new advanced model option is now available for handling complex code and long-running workflow tasks.

    Read original· x.com(opens in a new tab)
  3. Nvidia releases 120-billion-parameter Nemotron multimodal model

    Nvidia has launched the open multimodal model Nemotron 3.5 Super VL, utilizing a Mixture of Experts (MoE) architecture with 120 billion total parameters and 12 billion active parameters. The model integrates complex reasoning, tool calling, and image/video/text comprehension capabilities. Nvidia states that its agent task throughput on a single GPU can reach up to 5 times that of open models of the same scale.

    Why it matters You can achieve higher processing speeds and lower VRAM usage when building agents on a single graphics card.

    Read original· ithome.com(opens in a new tab)

04Research1 item

  1. Four Gemini 4 Argon agents defeat the Ender Dragon without human intervention

    Google DeepMind tested four Gemini 4 Argon agents beating Minecraft without any human intervention. The agents were placed directly into a randomly generated world and, without preset task divisions or strategies, independently completed collaborative exploration, threat warnings, material collection, and error experience logging.

    Why it matters Demonstrates the possibility of multi-agent systems collaborating to handle unknown, complex tasks without manual intervention.

    Read original· the-decoder.com(opens in a new tab)

05Industry2 items

  1. Anthropic Q3 revenue hits $16.8 billion, but growth slows

    Anthropic reported third-quarter revenue of $16.8 billion, a quarter-over-quarter increase of about 45%, which is lower than the growth rate of over 140% in the second quarter. The company's cash flow is currently positive, generating $1.70 in revenue for every $1 spent on compute. Some investors expect its IPO valuation could be adjusted downward to under $1.5 trillion.

    Read original· the-decoder.com(opens in a new tab)
  2. OpenAI engineering director arrested for allegedly planting eavesdropping device in meeting room

    Alforzan, an engineering director on OpenAI's product team, was arrested by the FBI and fired by the company for allegedly installing recording equipment behind a television in a San Francisco headquarters executive meeting room. Investigations revealed the employee had queried executive schedules in internal systems and used a family member's account to ask how to hide recording devices. OpenAI's security team used a large model to analyze clues and identify the suspect.

    Read original· x.com(opens in a new tab)