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    Qwen3-4B AI filter’s theoretical floor: about 6.6 seconds for 5,000 movie reviews on one H100

    Full Stack Data Lab says per-row API calls miss query-planning benefits in batch work.

    Shreya ShankarSS
    1 Source, 2h ago, first seen 2h ago

    TLDR

    Full Stack Data Lab estimates a theoretical minimum of about 6.6 seconds for one Qwen3-4B AI filter over 5,000 movie reviews on one H100. When sharing the lab’s blog in October 2026, the author said no system, including its open-source AI-SQL engine Quail, then came close. The author argues that per-row API calls miss query-planning benefits in batch work; the blog also examines how filter order changes the calculation.

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    1 Source

    Shreya Shankar@sh_reyaRT @sh_reya: Have you tried to use a decision model (like Jev) on thousands of rows? Calling an API once per row is a terrible idea for bat…2h

    1 Source

    Shreya Shankar@sh_reyaRT @sh_reya: Have you tried to use a decision model (like Jev) on thousands of rows? Calling an API once per row is a terrible idea for bat…2h