Google: Gemini 3.8 Flash
Google's flagship model. Long-context specialist with 1.0M window.
Scores by test
Methodology →What you need to know
Gemini 3.8 Flash distinguishes itself through high-reliability logic and formatting, achieving perfect 5/5 internal scores in structured output, strategic analysis, and tool calling. These metrics indicate a model capable of precise API interactions and complex reasoning tasks without the typical failure rates seen in smaller, faster models.
The pricing is aggressive for the performance level provided, with a blended cost of $3.00/MTok. While it ranks #17 overall out of 160 models, its ability to maintain a 5/5 score in faithfulness and persona consistency makes it a high-value option for developers who need stability and adherence to system prompts at a low cost.
Despite a massive 1.0M token context window, the model's internal long-context performance is rated 4/5, suggesting some degradation in retrieval or coherence as the window fills. Additionally, a 54.4% score on SciCode indicates moderate proficiency in scientific coding, though it is not a specialized scientific model.
Use this model if you are building agentic workflows that require strict structured data output and reliable tool calling on a budget. Skip this model if your primary requirement is high-precision classification or exhaustive retrieval across the full million-token context window.
Strengths — Top 3
Relative weaknesses — Bottom 3
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