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Google unveils Gemini 4 Argon, limits early access to cybersecurity testers

Google announced its new frontier AI model, Gemini 4 Argon, on Wednesday, ten months after Gemini 3's release. The model is initially being made available only to cybersecurity defenders in Google's Fairwind program, with wider subscriber and free-user access to follow later. Google says Gemini 4 Argon handles coding, multimodal tasks and reasoning, and performs especially well on business tasks like software engineering, cybersecurity and legal/finance work.

Samsung Galaxy Tab S12 Ultra brings few changes over Tab S11 Ultra

Samsung's Galaxy Tab S12 Ultra keeps the same 45W charging speed and 11,600mAh battery as its predecessor, the Tab S11 Ultra. The two tablets share identical IP68 ratings, thickness of 5.1mm, and weight of 692 grams, with the main difference being the S12 Ultra shipping with One UI 9.0 out of the box, an update the S11 Ultra will also receive soon.

OpenAI launches Dots AI agent exclusive to paid ChatGPT Pro subscribers

OpenAI unveiled Dots, an AI agent powered by GPT-6 Astra, at its DevDay conference, positioning it as a direct competitor to Meta's free Muse agent platform. Unlike Muse, which is available to any Meta account holder via a free virtual machine, Dots is limited to OpenAI's $20/month Pro plan and above, excluding most of ChatGPT's reported 1.2 billion users.

Google releases Gemini 4 Argon, its new flagship reasoning model

Google has launched Gemini 4 Argon, a frontier AI model built for deep reasoning in finance, coding, creative writing and cybersecurity tasks. Independent benchmarking firm Artificial Analysis found Argon matches OpenAI's GPT-6 Astra on its Intelligence Index at roughly 60 percent of the cost, with a notably lower hallucination rate of 15 percent. Google says it is already using Argon internally for quantum computing research, codebase migrations, and data center memory optimization, where it freed up 300 TiB of memory.

Google launches Gemini 4 Argon, leads 13 of 18 disclosed AI benchmarks

Google introduced Gemini 4 Argon, a new frontier AI model it says tops or ties rivals GPT-6 Astra and Claude Opus 5.5 on 13 of 18 disclosed benchmark categories. The model is initially limited to trusted cyber-defense partners and select pre-release testers, with wider rollout planned later. Google also says Argon supports up to 1 million output tokens, a sharp jump from the prior 64,000-token limit.

Google unveils Gemini 4 Argon but restricts access to internal testing

Google announced Gemini 4 Argon, a new frontier AI model it claims leads the industry in coding, knowledge work, and cybersecurity tasks. The model is not yet publicly available, though Google engineers are already using it internally, including for data center memory optimization and migrating large C/C++ codebases to Rust. Google released benchmark results showing Argon outperforming rivals like GPT-6 Astra, Fable 5.1, and Opus 5.5, and confirmed it will support a 1 million token output limit, up from 64,000 in earlier Gemini models.

Geekbench leak shows OpenAI's dots agent runs on 9-core AMD EPYC VMs

A pre-launch Geekbench 7 benchmark shared on X shows OpenAI's dots agent, powered by GPT-6 Astra, running on a nine-core slice of an AMD EPYC 9V74 virtual machine with roughly 9.73GB of memory. The leaked run scored 9,435 multi-core, higher than six post-launch runs found in Geekbench's public database ranging from 8,135 to 8,991. Dots launched Tuesday at OpenAI's DevDay for Pro and Business Premium users, giving each agent its own cloud computer, browser, and preloaded software including Blender, GIMP, and Python.

Weave Router 2.0 matches GPT-6 Astra performance at half the cost

Weave OS released Weave Router 2.0, an open-source model router that dynamically switches between LLMs for coding agents like Claude Code or Codex. On Terminal Bench 4.0 and SWE Atlas benchmarks, the router matched GPT-6 Astra's pass rates while running at roughly 52-54% of its cost and 2.2-2.5x faster. The company attributes the gains to a new routing architecture, a larger training dataset, and improved cache-eviction calculations.

OpenAI's new Dots AI agent stalls during live DevDay demo

At its DevDay conference in San Francisco, OpenAI unveiled a new always-on AI agent called Dots, powered by its GPT-6 Astra model. During a live demonstration, product team member Holly Li called the agent by phone and asked for a testing update, but it took an extended pause and never gave a substantive answer, only repeating that it was 'still checking.'

OpenAI launches always-on 'Dots' agents at DevDay, day after delaying GPT-6.1 Astra

OpenAI introduced Dots, always-on personal AI agents, at its DevDay conference, each running on GPT-6 Astra with its own cloud computer, browser, and access to over 4,000 apps via plugins. The launch came less than a day after OpenAI delayed GPT-6.1 Astra over safety concerns, with safety chief Saachi Jain noting the model had grown more persistent at completing tasks in ways that raised concerns about unauthorized actions. Users can reach their dot via ChatGPT, Slack, or Teams, with background research restricted to read-only tools while purchases require explicit approval.

OpenAI launches always-on 'Dots' AI agents powered by GPT-6 Astra

OpenAI unveiled Dots at DevDay 2026, always-on personal AI agents that keep working in the background after a chat ends. Each Dot runs on GPT-6 Astra with its own cloud computer and browser, connects to over 4,000 apps, and can be reached consistently through ChatGPT, Slack, or Microsoft Teams, with texting support coming soon. The feature is rolling out gradually to Pro, Business Premium, and Enterprise subscribers in select markets.

OpenAI releases GPT-6.1 Sol, a cheaper model nearing Astra's performance

OpenAI has launched GPT-6.1 Sol as part of its DevDay announcements, positioning it as a lower-cost alternative to its flagship GPT-6.1 Astra model. The company says Sol performs comparably to Astra on coding, professional Q&A, document handling, computer use and research tasks, at roughly one-fifth the cost. OpenAI also reports that Sol's rate of factual errors in lower-effort responses dropped from 11.4% with GPT-6 Sol to 7.7% with the new version.