The Jalapeño accelerator generates roughly double the tokens per megawatt of power compared to the GB300, and at low batch sizes hits 700 tokens per second per user versus competitors' 350. It outperforms on both throughput and energy efficiency.
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And so whether you're optimizing for the y-axis or the x-axis, Jalapeño is beating the GV300 right now on the DeepSeek model, which implies something like, if you were to fix the interactivity per user, so everybody sees 100 tokens per second or 50 tokens per second, and I zoom in on like exactly that part of the curve, we're basically seeing that Jalapeño has double the amount of tokens that it can produce per megawatt, implying— 2 times more revenue, 2 times more profitability, whatever you wanna say, from an inference endpoint serving provider. And then if you look at the far right side of this curve across the x-axis, and you see that at a very low batch size, they can go all the way to 700 tokens per second per user, and you compare that to where the others peak out at 350, this is once again double the performance. And I think the conclusion is that they're basically winning on both sides of the curve.