@jeremyphoward
RT @haoailab: (1/5) FP4 hardware is here, but 4-bit attention still kills model quality, blocking true end-to-end FP4 serving. To fix that,…
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"text": "(1/5) FP4 hardware is here, but 4-bit attention still kills model quality, blocking true end-to-end FP4 serving.\nTo fix that, we propose Attn-QAT, the first systematic study of quantization-aware training for attention.\n\nThe result: FP4 attention quality is comparable to BF16 attention with 1.1x–1.5x higher throughput than SageAttention3 on an RTX 5090 and 1.39x speedup over FlashAttention-4 on a B200.\n\nBlog: https://t.co/NxVSXKWEgI\nCode: https://t.co/6irFgQ7GeM\nCheckpoints: https://t.co/GsrzbJlRY8",
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