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Dev.to
5/10/2026
Flux Attention halves inference cost on long contexts

Flux Attention halves inference cost on long contexts

Short summary

Flux Attention uses layer-wise dynamic sparse routing to cut LLM inference costs by 2-3x on long contexts while preserving reasoning quality. Training the lightweight router takes just 12 hours on 8 A800s with negligible 0.20ms per-layer overhead. Available on Hugging Face; benchmark your target context lengths before production deployment.

  • •Achieves 2-3x speedup (2.8x prefill, 2.0x decode) through layer-wise routing between full and sparse attention
  • •Router training is parameter-efficient (12 hours on 8-GPU A800), overhead negligible (0.20ms per layer)
  • •Production-ready: released on Hugging Face and ModelScope; requires benchmarking on your specific hardware and context lengths

Generated with AI, which can make mistakes.

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