Google's latest drop was massive, but the benchmark data was spread across a dozen different slides. I stitched all the data together into a single, high-res comparison table to help understanding the lineup, and make choosing an API model a bit easier.

Model Selection Guide:

Gemini 3 Deepthink (Based on Pro, but reasons for longer): Maximum reasoning, Olympiad-level math, and complex code generation. Provides similar responses as Pro model but more precise. It is now available as an option in the "Thinking level" for Ultra users.
Gemini 3.1 Pro: Can be used for highly complex, multi-step agent workflows, and complex math/coding problems.
Gemini 3.5 Flash (Recommended): The new sweet spot. Near-Pro performance and tool-use, but with Flash-level response times. Use its reasoning mode for advanced math/coding.
Gemini 3 Flash: Cheaper than 3.5 Flash as of now, with reliably fast response times. Use for general tasks and coding.
Gemini 3.1 Flash-lite: Ultra fast. If you just need massive amounts of text categorized, summarized, or parsed instantly then use this. For general usage, simple math queries and all, it is still pretty quick and useful. But if you care for intelligence, Gemma 4 31B is a little better, more cheaper, but is considerably slower.

Sources:

https://arcprize.org/leaderboard
https://ai.google.dev/gemma/docs/core/model_card_4
https://ai.google.dev/gemini-api/docs
https://deepmind.google/models
https://artificialanalysis.ai/models
https://blog.google/innovation-and-ai/models-and-research/gemini-models/

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A complete breakdown of the new Gemini ecosystem (Scores, Prices, and Use Cases)

Model Selection Guide:

Sources: