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Flash-MoE streams 35B models onto iPhone

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Flash-MoE streams 35B models onto iPhone
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// 1h agoVIDEO

Flash-MoE streams 35B models onto iPhone

A Better Stack video demonstrates Flash-MoE running Qwen3.5-35B-A3B on an iPhone at roughly 11 tokens per second. The open-source engine streams only the active Mixture-of-Experts weights from storage, avoiding the need to fit the entire model in RAM.

// ANALYSIS

Flash-MoE turns storage bandwidth into usable model capacity, making genuinely large local models viable on mobile hardware.

  • Qwen3.5-35B-A3B has 35B total parameters but only about 3B active per token, making it an ideal SSD-streaming target.
  • The trade-off is clear: lower RAM requirements come with per-token storage I/O, latency sensitivity, and thermal constraints.
  • Its pure C, Objective-C, and Metal implementation keeps the runtime lightweight and tightly aligned with Apple Silicon.
  • iOS ports require specialized memory entitlements, pread-based loading, and model-management work, so this is still an engineering demo rather than a turnkey consumer app.
  • The approach could make private, offline inference far more capable as mobile flash storage and bandwidth improve.
// TAGS
flash-moeinferencemoeedge-aistreamingopen-sourcelocal-first

DISCOVERED

1h ago

2026-09-16

PUBLISHED

2h ago

2026-09-16

RELEVANCE

10/ 10

AUTHOR

Better Stack