Liquid AI LFM3's hybrid architecture: 6 global attention layers, 256K context, 25% faster inference
cneuralnetwork · x · 2026-10-28
After reading Liquid AI's launch post, the author argues hybrid architectures are the next big thing: LFM3's 1.7B model uses 13 gated convolution layers, 5 sliding-window attention layers, and only 6 global attention layers — cheap convs for local patterns, SWA for nearby dependencies, global attention reserved for long-range context. This yields a 256K context window, 1GB weights at 4-bit, and reportedly 25% faster inference at 8K context vs LFM2-1.2B on edge devices.
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