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We just open sourced a tiny GPT-style cognitive core built in pure Rust.See our repository

Self-contained agents that self-organize

Coding is verifiable formal thinking, try our in-terminal agent Ante built from scratch with first principles.

$curl -fsSL https://ante.run/install.sh | bash

One install command. Pick a model. Start coding. No accounts, no configuration files, no setup guides.

Step 01

Go offline in one command

Type /offline-mode — Ante installs a local inference engine. No API keys, no internet.

Step 02

Configure the model

Choose your model, set context window, enable thinking mode. Tuned to your hardware.

Step 03

Agent does the work

Give it a task. The agent reads your codebase and produces working output — fully offline.

MEET ANTE

AI-native, cloud-native,
local-first agent runtime

Built from the ground up in native Rust — a single self-contained binary with no external dependencies. Designed for cellular-native agents: lightweight enough to run by the thousands and reliable enough that the system self-heals when any one fails.

Lightweight agent core

A single lightweight binary with zero runtime dependencies. Built for minimal overhead and maximum throughput — the ideal runtime for orchestrating agents at cellular scale.

Native local models

Run models entirely on your machine with built-in llama.cpp integration. No API keys, no internet, no data leaving your device.

Zero vendor lock-in

Bring your own API key, subscription, or local model. Switch between providers freely — Anthropic, OpenAI, Gemini, Grok, Open Router, and more. No account required.

Peak memoryless than Claude Code
Avg CPUless than Claude Code
Disk I/Oless total I/O generated
Binary~15 MBSingle Rust binary, zero deps
20 parallel tasks · same model · same promptsSee benchmark details →

Built on first principles

Ante is designed for cellular-native agents — like cells in a living organism, tiny and expendable, massively replicated. Everything we build serves this thesis.

Lightweight

Hundreds of agent replicas can't each cost gigabytes. Every byte per instance matters at scale — so we maintain a tight, tiny core.

Reliable

The return on reliability is non-linear. There's a phase transition — and you need to be on the right side of it.

Closed-loop

Declarative intent, automatic reconciliation. Individual agents are expendable; the organism persists.

Minimal cognitive load

Fewer concepts to learn, fewer knobs to turn. If a feature needs a paragraph of explanation, it's probably too complex.