We’re introducing new Gemini models, including Gemini 3.6 Flash, 3.5 Flash-Lite and 3.5 Flash Cyber. Our newest Gemini models deliver the efficiency, latency, and reliability to build AI agents at scale.
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Adding first-class observability dashboards built into the model API would be huge. Real-time token usage, latency breakdowns, and failure pattern detection per agent run would make it way easier to debug and optimize at scale.
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Finally gave the new Flash a spin on a quick agent task and the latency drop was honestly noticeable, made the whole loop feel snappier than I expected.
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I noticed this change. It's good to have explanations of these changes I don't think the models are necessarily intuitively understandable. I think a rolling explanation somewhere may be useful, especially when it changes often.
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How the reasoning of 3.6 compare to previous 3.5 flash models for task like high level coding, edits, fixes and reviews?
Adding first-class observability dashboards built into the model API would be huge. Real-time token usage, latency breakdowns, and failure pattern detection per agent run would make it way easier to debug and optimize at scale.
Finally gave the new Flash a spin on a quick agent task and the latency drop was honestly noticeable, made the whole loop feel snappier than I expected.
I noticed this change. It's good to have explanations of these changes I don't think the models are necessarily intuitively understandable. I think a rolling explanation somewhere may be useful, especially when it changes often.