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Google releases series of new cheaper Gemini models

Google releases series of new cheaper Gemini models
Photo: Justin Sullivan/Getty Images

Google on Tuesday introduced three new Gemini AI "flash" models that all have a focus on efficiency, amid a surge in use of open-models that can be more affordable. Why it matters: The AI deployment race has shifted from benchmark bragging rights to who can provide the best model at the lowest price. The new models include: Gemini 3.6 Flash: a faster, cheaper successor to 3.5 Flash that Google says uses up to 17% fewer output tokens while...

Google on Tuesday introduced three new Gemini AI "flash" models that all have a focus on efficiency, amid a surge in use of open-models that can be more affordable.

Why it matters: The AI deployment race has shifted from benchmark bragging rights to who can provide the best model at the lowest price.

The new models include:

  • Gemini 3.6 Flash: a faster, cheaper successor to 3.5 Flash that Google says uses up to 17% fewer output tokens while improving coding, reasoning and multimodal performance.
  • Gemini 3.5 Flash-Lite, an even lower-cost model designed for high-volume AI agents and document processing.
  • Gemini 3.5 Flash Cyber, a security-focused model built to identify and patch software vulnerabilities, initially available only to governments and selected partners through Google's CodeMender platform.

Yes, but: The release does not include Gemini 3.5 Pro, a more powerful model that Bloomberg last week reported was months behind schedule.

  • Google Tuesday said Gemini 3.5 Pro is in testing and will be broadly available once it's ready, while Gemini 4 is in pre-training.
  • Shares of Google parent Alphabet were down 0.8% midday Tuesday and nearly 6% since Thursday.

Zoom in: Each of the models introduced Tuesday appears to address a key focus for enterprise customers.

  • 3.6 Flash costs less per token than its predecessor while improving coding accuracy and reducing unnecessary reasoning steps, which has become an increasingly important metric as companies try to rein in AI costs.
  • Flash-Lite targets the growing market for AI agents that need to execute millions of relatively simple tasks cheaply rather than maximize benchmark performance, a sign of the increase in enterprise agent usage.
  • The cybersecurity model reflects Google's broader push to commercialize DeepMind research through enterprise security products.

Zoom out: Rather than betting on a single flagship model, Google is building a portfolio optimized for different workloads, prices and industries.

State of play: The releases arrive during one of the fiercest recruiting wars in Silicon Valley.

  • Google has spent months trying to retain key DeepMind researchers as top talent have left the company, citing its ties with the U.S. military.
  • Frontier competitors, meanwhile, including OpenAI, Meta and Thinking Machines, have been aggressively recruiting top talent with lucrative compensation packages.
  • Meta alone has hired a number of prominent Google researchers in recent months, highlighting that the battle for AI leadership increasingly hinges on people as much as models.

The bottom line: The AI race is increasingly becoming less about producing the single smartest model and more about giving developers and businesses choice about which model is best for the job.

Read full story on Axios

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