The Problem: Currently, it is difficult to distinguish between a “hanging” request and a high-latency response from complex models like Gemini 3.1 Pro. Without specific timing data, developers cannot effectively design system architecture for “agentic” workflows.
Specific Example: We are consistently seeing Gemini 3.1 Pro take over 60 seconds to complete a single response. Because the logs don’t show the breakdown of that minute (e.g., Prompt Processing vs. Thinking vs. Generation), we are struggling to:
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Set accurate client-side timeouts to avoid killing valid but slow requests.
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Trigger automated fallbacks to Gemini 3.1 Flash when Pro exceeds a specific latency threshold.
Proposed Metrics:
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Time to First Token (TTFT): To measure initial responsiveness.
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Total Wall-Clock Time: Total duration from request to completion.
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Thinking Latency: Time spent generating “thought” tokens versus output tokens.
Providing this transparency in AI Studio would allow us to benchmark model performance accurately before migrating to Vertex AI or production environments.