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A possible memory-bandwidth trade-off in OpenAI's Jalapeño chip
A user flags HBM4 and the absence of super-long-context testing as caveats to Jalapeño–Blackwell comparisons.
TLDR
A user's notes suggest OpenAI's Jalapeño chip exposes more hardware to software to maximize effective memory bandwidth, making kernels harder to write. They think OpenAI is betting AI-assisted kernel generation and search can handle that complexity. They say Jalapeño seems to beat Blackwell on performance per watt, but its HBM4 makes Rubin a better comparison, and testing wasn't done at super-long context. Its figures also omit speculative decoding and MTP, which the user calls a handicap.
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