Google released three new Gemini models—3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber—optimized for agentic workloads with lower latency and reduced token consumption. Gemini 3.6 Flash cuts output tokens by 17% overall and up to 65% on coding benchmarks, with output pricing dropping from $9.00 to $7.50 per 1M tokens, while 3.5 Flash-Lite achieves 350 output tokens per second at $0.30/$2.50 per 1M. Developers can now build cheaper, faster multi-agent systems with built-in computer-use capabilities, though the specialized Cyber model for vulnerability detection remains gated to governments and trusted partners.
Google released three new Gemini models—Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber—focused on efficiency and cost reduction, but notably omitted the long-awaited Gemini 3.5 Pro. Gemini 3.6 Flash reduces token usage by up to 17% compared to its predecessor while improving coding and multimodal performance. The delay to Gemini 3.5 Pro, attributed to internal performance challenges, leaves Google behind competitors OpenAI and Anthropic in flagship model releases, though the company says Pro is in partner testing and aims to ship soon.
Google released Gemini 3.6 Flash, replacing the earlier 3.5 Flash version, along with a new cybersecurity-focused AI model, but delayed the expected Gemini 3.5 Pro launch beyond June. Gemini 3.6 Flash offers marginal improvements in capability and code generation based on user feedback from the 3.5 release. The update reflects Google's prioritization of efficiency and cost control as customers worry about token expenses.
Google released three new Gemini models: Gemini 3.6 Flash with 17% better token efficiency than 3.5 Flash, Gemini 3.5 Flash-Lite achieving 350 output tokens per second, and Gemini 3.5 Flash Cyber for cybersecurity tasks. Gemini 3.6 Flash costs $1.50 per million input tokens and $7.50 per million output tokens, reducing overall agentic task costs. These models enable developers to build more efficient and cost-effective AI agents with improved performance on coding, knowledge work, and security tasks.
Google released three new Gemini models: Gemini 3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber, designed for efficient AI agents and production workloads. Gemini 3.6 Flash reduces output token usage by 17% compared to 3.5 Flash and costs $1.50/1M input tokens and $7.50/1M output tokens, while 3.5 Flash-Lite runs at 350 output tokens per second at $0.3/1M input and $2.5/1M output tokens. These models enable developers to build more cost-effective agentic workflows with improved performance on coding, knowledge work, and security tasks.
Google released three new Gemini models—3.6 Flash, 3.5 Flash-Lite, and 3.5 Flash Cyber—but delayed its flagship 3.5 Pro model, originally promised in June and still in testing weeks past deadline. Gemini 3.6 Flash reduced output token costs from $9 to $7.50 per million tokens and uses 17% fewer tokens in agentic workflows, with scores of 49% on software engineering benchmarks versus competitors' 54–70%. The delayed Pro model means developers must choose between mid-range options now or wait for the flagship, while 3.5 Flash Cyber remains restricted to government and partner pilots.
Google launched Gemini 3.5 Flash Cyber, an AI model designed to find and patch security vulnerabilities as a lower-cost alternative to larger systems like Anthropic's Mythos. The model will initially be available to governments and trusted partners through CodeMender, Google's security-focused coding agent, which can call it multiple times at high speed and low cost. This enables AI agents to scan more code paths and identify vulnerabilities more efficiently than with expensive larger models.
Google is developing a specialized server chip called Frozen designed to run Gemini AI models natively. The chip is being built in-house to optimize performance for Google's Gemini large language models. This gives Google greater control over AI inference hardware and reduces reliance on third-party chip providers for its own AI services.
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