Xenova showed the Pi coding agent running LFM3-1.7B entirely in the browser at more than 300 tokens per second on an M4 Max, using custom WebGPU kernels and 4-bit weights, with nothing sent to a server. Osaurus also shipped day-zero LFM3 support, showing t...
VQV Signal
Liquid AI's LFM3-1.7B runs a coding agent inside the browser
Xenova showed the Pi coding agent running LFM3-1.7B entirely in the browser at more than 300 tokens per second on an M4 Max, using custom WebGPU kernels and 4-bit weights, with nothing sent to a server. Osaurus also shipped day-zero LFM3 support, showing t...
Xenova showed the Pi coding agent running LFM3-1.7B entirely in the browser at more than 300 tokens per second on an M4 Max, using custom WebGPU kernels and 4-bit weights, with nothing sent to a server. Osaurus also shipped day-zero LFM3 support, showing the model analyzing a case file fully offline. Also:...
Teams using AI at work may want to compare this against current productivity and review workflows.
VQV organizes public signals from inspectable sources. It does not independently verify the underlying report.
Signal Strength reflects source quality, relevance, freshness and evidence. Public Interest helps organize discovery; it is not proof of truth.
Public Interest components
VQV surfaced this signal because it is recent, relevant to AI Chips, connected to Scobleizer News Pulse (X).
No login, cookies, social SDKs, or automatic posting.