Samuel Zeng (@SamuelZengML)
@SamuelZengML
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Introducing Edge0-145B and Edge0-120B, @Edge0_AI’s first device-native 100B-class foundation models with open weights.
Cloud-level intelligence on your laptop. Free, offline, and fast enough for real vibe coding.
- Smart: beats Claude Opus 4.6 on Terminal-Bench 2.1 (86.5% vs. 78.2%)
- Light: needs just 29G memory, 1/3 of a standard setup (100G+)
- Fast: decodes 75+ toks/s, prefills 1050+ toks/s on RTX Spark and Mac.
- Steady: handles 128K–256K tokens of context without slowing down, even on long tasks
Frontier-class agentic coding. No cloud API. No token bill. Your code and data never leave your machine.
Open weights are live on @huggingface. Run it locally or plug it into your favorite coding agent.
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Three weeks ago, we released the first version of Edge0:
“A 35B language model running on a local device, using only 1–2.5 GB of peak memory.”
Today, we’re taking the next step.
We’re open-sourcing the Edge0 app layer—now available on:
📱 iOS
🖥️ macOS
🤖 Android
🪟 Windows
One app. Four platforms. Fully on-device.
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Speech recognition is easy—until you ask it to listen forever.
Today we’re open-sourcing Audio8 ASR Infinite:
Ultra-low latency, unlimited audio, 24/7 transcription, no drift.
Built-in semantic turn detection keeps it listening like a human ear.
New SOTA for streaming ASR.
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A 35B language model running on an iPhone using only 1–2.5 GB of peak memory.
No cloud. No remote server. No desktop GPU.
Today, we’re open-sourcing Edge0 — a framework for running large AI models fully on-device.
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