Google has released Gemini 4 Argon, an AI model aimed at tasks like coding, research, writing, and especially defensive cybersecurity. Google says Argon can autonomously find, validate, and patch critical software vulnerabilities. The model is being rolled out only to a select set of cyber partners via its Fairwind Program, and Google positions it as outperforming other recent models on Vals benchmarks.
Google began rolling out Gemini 4 Argon to vetted cybersecurity defenders through its Fairwind Program, limiting outside access for now. The rollout is priced at $2 per million input tokens and $10 per million output tokens at launch. The model’s access and safeguards change so defenders get Argon first with cyber guardrails while later releases and commercial subscriptions are planned for other users.
Google announced Gemini 4 Argon, an AI model it says is strongest for coding, knowledge work, and cybersecurity, but it is not available for public use yet. Google says Argon saves 300 TiB of memory across its data centers and reports 77.9 percent on the DeepSWE v1.1 benchmark. Access is limited to Google engineers for now, while internal use and Rust-migration/benchmarking efforts continue until broader availability.
Google announced Gemini 4 Argon as its flagship model but is limiting access while it gathers early feedback and adjusts guardrails. The model is priced at $2 per million input tokens and $10 per million output tokens during an introductory period, before rising to $4 and $20. Access will roll out first to Fairwind participants, then paid API and AI Ultra subscribers, and only later to developers, enterprises, and consumers; overall it performs strongly on knowledge-work benchmarks but is weaker on some coding and cybersecurity measures.
Google launched Gemini 4 Argon, a frontier AI model aimed at careful reasoning and long-horizon professional tasks. It supports up to 1 million output tokens. Access will expand gradually via trusted testing and safety safeguards.
The newsletter says Claude 5.5 is both brilliant and confusing, while also describing it as “very hungry.”
It specifically calls out the Claude 5.5 version as unusually demanding.
As a result, readers are warned to expect strong performance but also potential confusion and higher resource/consumption needs.
OpenAI halted its Astra update and instead released GPT-6.1 Sol at DevDay as a lower-cost option aimed at similar coding and professional performance. GPT-6 Sol is $3.26 per task versus $0.72 per task for Sol, and Sol scores 52 points in the Artificial Analysis Intelligence Index, placing 10th among 222 models. The change moves users toward Sol because it is cheaper to run (and has cheaper cache pricing) while still trailing Astra by about 1 point and slightly reducing hallucinations.
OpenAI announced DevDay 2026 updates including dots, ChatGPT Spaces, GPT-6.1 Sol, and multiple platform APIs and plan changes. Ultrafast mode claims up to 300 tokens per second in Codex, alongside Decisions API and other tooling. These updates expand agent-driven app integrations, shift pricing and plan multipliers, and add new model capabilities and faster coding/classification features for developers and businesses.
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