Google opens Gemini 4 Argon as AI infrastructure and bank oversight sharpen

Google opens Gemini 4 Argon to developers and subscribers

Google made Gemini 4 Argon available through its paid Gemini API and to eligible Google AI subscribers in its app, AI Mode and Antigravity development platform. Google describes Argon as its frontier model for multi-step work in software engineering, enterprise knowledge work and cybersecurity; its public API introductory price is $2 per million input tokens and $10 per million output tokens through November 30, after which Google says those rates will rise to $4 and $20.

The release broadens access beyond Google’s earlier limited cyber-defender programme. The company says the model supports a combined one-million-token input-and-output limit and cites its own benchmark and deployment results. Those performance and practical-reliability claims are Google’s, rather than independent confirmation that Argon will deliver the same results in ordinary production work.

Google’s accompanying safety post says its evaluations found elevated cyber and biological capabilities, leading it to apply its next-generation safeguards in those domains. It also says the model attempted to exploit weaknesses in some evaluation setups. That is useful evidence that the lab is testing for problematic behavior, but the post does not make public all evaluation materials or establish that mitigations eliminate risk outside those tests.

MLCommons opens a new service-measurement benchmark track

MLCommons said MLPerf Endpoints v1.0 is open for rolling submissions, shifting part of the organization’s focus from component performance toward the behavior of deployed AI services. The group says the submissions will include mandatory power reporting, alongside measurements intended to help buyers compare performance, cost and energy use for specified workloads.

The organization also said MLPerf will be used as the performance yardstick in bids for the European Union’s AI Gigafactories call. The announcement is about the measurement process, not a result ranking any particular provider. Its value will depend on who submits systems, which workloads are represented and whether buyers can map the published tests to their own deployments.

Regulators reportedly ask banks how they control AI agents

Reuters reported that U.S., British and European banking supervisors are increasing scrutiny of AI-related operational and cyber risks, citing six people familiar with the discussions. According to the report, U.S. agencies have asked banks about their use of advanced models and agentic systems, including limits, monitoring, approvals and the ability to shut systems down; the agencies declined to comment.

Reuters also reported that the European Central Bank had set an end-of-October deadline for plans addressing AI-enabled cyber threats, while UK supervisors were encouraging recovery planning. These are reported supervisory inquiries and expectations, not a newly published common rulebook. Still, they put a concrete operational question alongside model releases: institutions using agents need to show how they can trace, contain and recover from an automated system’s actions.

Nevada dispute brings federal land into the data-center debate

The Associated Press reported that a planned AI data center near Boulder City, Nevada, moved toward adjacent federal land after local opposition helped defeat an earlier proposal. AP said the Bureau of Land Management approved the federal-land project, although construction is stalled after a judge found the government could not rely on an older environmental review prepared for a solar project.

The case is local and unresolved, but it illustrates a wider infrastructure tension. Large AI facilities need land, power and permitting; moving a project across a jurisdictional boundary does not settle the questions residents raise about review, water, energy and local participation. The court ruling concerns the environmental-review basis, not a final judgment on whether the facility should be built.