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    Tweet Claims OpenAI Jalapeño Outperforms Blackwell Chips

    Rohan Paul shares Semianalysis details on OpenAI's upcoming Jalapeño chips.

    RP
    1 Source, 31d ago, first seen 31d ago

    TLDR

    Rohan Paul posted about a Semianalysis report on OpenAI's Jalapeño chips planned for deployment in the company's own compute by the end of 2026. The post states that Jalapeño smokes every other chip without Multi Token Prediction, while competing chips on the chart use their best performing configs with MTP. A generated headline in the same post indicates the Jalapeño chip outperforms Blackwell.

    Combined views

    9.4K

    1 Source, first seen 31d ago

    Combined views

    9.4K

    1 Source, first seen 31d ago

    77 likes
    77 likes
    16 comments
    22 saves
    12 reposts

    Sentiment

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    16 comments
    22 saves
    12 reposts

    Sentiment

    Positive——Negative

    Summary

    Not enough discussion yet.

    No sentiment analysis available yet.

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    1 Source

    @rohanpaul_aiSemianalysis on OpenAI's new Jalapeño chips that will be deployed inside its own compute by the end of 2026. "Jalapeño smokes every other chip. All this is done without Multi Token Prediction (MTP), while the other chips on the chart are the best performing configs of each respective SKU, all with MTP" Jalapeño shifts the entire latency–efficiency Pareto frontier upward: at ~100 tok/s/user it delivers ~11M tok/s/MW, roughly 2× the best Blackwell-class configs at comparable interactivity. The kicker: that’s STP (Single-Token Prediction) with no speculative decoding, while the competing curves are already using MTP.

    1 Source

    @rohanpaul_aiSemianalysis on OpenAI's new Jalapeño chips that will be deployed inside its own compute by the end of 2026. "Jalapeño smokes every other chip. All this is done without Multi Token Prediction (MTP), while the other chips on the chart are the best performing configs of each respective SKU, all with MTP" Jalapeño shifts the entire latency–efficiency Pareto frontier upward: at ~100 tok/s/user it delivers ~11M tok/s/MW, roughly 2× the best Blackwell-class configs at comparable interactivity. The kicker: that’s STP (Single-Token Prediction) with no speculative decoding, while the competing curves are already using MTP.