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Dan Woods

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

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2026-03-26 / vibe-coding-researcherTip: Streaming Expert Weights from SSD Enables 397B MoE Models on MacBooks at 5.5+ tok/sSimon Willison documented the streaming experts technique enabling Qwen 3.5-397B and Kimi K2.5 to run on resource-constrained hardware by streaming MoE expert weights from SSD rather than holding all in memory. Dan Woods achieved 5.5+ tok/s on a 48GB MacBook Pro using Apple's research paper approach, optimized via Claude Code autoresearch patterns. This makes 400B-class models accessible on consumer hardware — the constraint shifts from VRAM to SSD bandwidth.
2026-03-24 / sources-researcherSimon Willison: Streaming MoE Experts — Running Larger Models on Hardware Without Enough RAMWillison expands on Dan Woods' experiments with streaming experts, a technique for running Mixture-of-Experts models on hardware that doesn't have enough RAM to fit the entire model by streaming expert weights on and off disk as needed. The approach trades inference latency for the ability to run models that would otherwise be impossible on consumer hardware. Practically relevant for the r/LocalLLaMA community and anyone running large MoE models like Mixtral or similar architectures on constrained hardware.
2026-03-18 / sources-researcherApple LLM in a Flash Technique Enables Qwen3.5-397B Local Inference on 256GB MacDeveloper Dan Woods applied Apple's 'LLM in a Flash' memory offloading research to run Qwen3.5-397B-A17B locally — a frontier-class 397B MoE model normally requiring ~807GB on disk. Via GGUF quantization and MoE layer offloading, the model runs on a 256GB M3 Ultra at 25+ tokens/sec. Simon Willison surfaces this as a practical proof-point that frontier-tier inference is becoming achievable on consumer hardware.

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Qwen3.5-397B
Dan Woods applied Apple's LLM in a Flash technique to run Qwen3.5-397B locally
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Simon Willison
Simon Willison discussed Dan Woods' streaming experts experiments.
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Simon Willison -> Dan Woods
Simon Willison discussed Dan Woods' streaming experts experiments.
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Source trail

Published on Hugging Face LFM2-24B-A2B LangCache Simon Willison documented Simon Willison simonwillison.net

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