Samuel Zeng

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.

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.

Introducing Audio8-TTS-Realistic, @Edge0_AI’s new open-weight speech model: realistic, zero-shot voice cloning in just 0.6B parameters.

• Human-like prosody and expressive delivery
• Clones a voice from one short clip, in 23 languages
• 601M params: small enough to fine-tune and serve affordably

Currently #1 on the Hugging Face TTS Arena, where people vote blind on which voice sounds more human.

Open weights are available now on @huggingface. Try it free.

Awesome!

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.