Android is rolling out enhanced scam-defense features in Google Messages that evaluate suspicious conversations with unrecognized senders using cloud-based Gemini AI models. The enhanced protection setting is scheduled to roll out in the coming weeks. As a result, Google Messages will add additional safeguards beyond its existing Scam Detection feature by analyzing likely scam intent during the chat flow.
Google made its Gemini 4 Argon multimodal language AI model broadly available via the Gemini API.
API pricing is discounted to 2/10 per 1M tokens for a limited time.
The model can now be used across paid Gemini API tiers and for select subscribers under the lower-cost pricing window.
Gemini 4 Argon is being rolled out to selected users with benchmark results showing it matches GPT-6 Astra on an Artificial Analysis Index score while improving on lower hallucinations and agentic evaluations. It costs $1.99 per Intelligence Index task during a 50% launch discount (before discount, $3.98 after the promo ends). The promotion and cache discounts lower per-task cost and reduce hallucination rates, while accuracy is reported at 50%.
Google launched Gemini 4 Argon for developers and enterprises through API and AI Studio/AI Ultra, plus for consumers via Google apps and Search AI Mode, and also rolled it out to partners for trials. The model is priced at $2 per million input tokens and $10 per million output tokens at launch. Access and pricing shift as paid users and enterprise developers can start using Argon immediately across Google’s platforms, with some programs expanding access to additional partners and a free 6-month high-usage tier for 10,000 scientists.
Gemini 4 Argon was released globally as a GA coding model, with access expanding beyond an earlier claim about cybersecurity-only availability. Introductory API pricing is $2 per million input tokens and $10 per million output tokens, with cached inputs discounted 95% and rates scheduled to rise to $4/$20 after November 30. The rollout broadens where Argon can be used (API, Gemini apps/search, and developer tools) and drives new public benchmark and cost comparisons.
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