[NEWSLETTER]score: 0.86
MiniMax M3 Claims 15.6x Faster Decode at Long Contexts via Sparse Attention
May 29, 2026
MiniMax's upcoming M3 models use a new sparse attention mechanism delivering 15.6x decode speed improvement at long contexts compared to standard attention, which the company says makes ultra-long-context agent deployment economically viable. No release date or full architecture details have been published yet.
HOW THIS AFFECTS YOU
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builderIf the M3 performance holds, long-context agent pipelines that were previously cost-prohibitive become deployable — worth tracking the release closely.
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researcherA 15.6x decode speedup at long contexts via sparse attention is a significant efficiency claim worth scrutinizing — architecture and ablation details will determine whether this generalizes.
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founderUltra-long-context agents at viable inference cost removes a key constraint on agentic product design; M3 could shift what's buildable without custom infrastructure.