Gemini 3.5 Flash
Google's mid-tier model. Long-context specialist with 1.0M window.
Scores by test
Methodology →What you need to know
Gemini 3.5 Flash distinguishes itself through high-reliability execution of complex logic and formatting. It achieves perfect 5/5 scores across structured output, tool calling, agentic planning, and strategic analysis, making it a robust engine for autonomous workflows and API-driven integrations.
The model provides a massive 1.0M token context window, though its internal performance in long-context tasks (4/5) slightly trails its capabilities in structured data and multilingual processing. While it excels at complex reasoning, it is less effective at simple classification and safety calibration, where it scores 3/5 and 2/5 respectively.
At a blended cost of $7.13/MTok, the model is priced as a mid-tier option. It offers a high performance-to-cost ratio for developers needing agentic capabilities and strict output formatting without the expense of frontier-class models.
Use this model if your application requires reliable tool calling, complex strategic planning, or processing of very large datasets. Skip this model if your primary need is high-precision classification or if your use case requires strict safety guardrails.
Strengths — Top 3
Relative weaknesses — Bottom 3
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