Self-contained agents that self-organize | Antigma
Skip to main content<br>We just open sourced a tiny GPT-style cognitive core built in pure Rust.See our repository→
Self-contained agents that self-organize<br>Coding is verifiable formal thinking, try our in-terminal agent Ante built from scratch with first principles, with Antix Console for account, API keys, and dashboard access.
Start with AnteSign in to Console
$curl -fsSL https://ante.run/install.sh | bash
Quick start<br>One install command. Pick a model. Start coding. No accounts, no configuration files, no setup guides.
Step 01Go offline in one command<br>Type /offline-mode — Ante installs a local inference engine. No API keys, no internet.
Step 02Configure the model<br>Choose your model, set context window, enable thinking mode. Tuned to your hardware.
Step 03Agent does the work<br>Give it a task. The agent reads your codebase and produces working output — fully offline.
MEET ANTE
AI-native, cloud-native,<br>local-first agent runtime<br>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<br>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<br>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<br>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 memory7×less than Claude Code
Avg CPU9×less than Claude Code
Disk I/O5×less total I/O generated
Binary~15 MBSingle Rust binary, zero deps
20 parallel tasks · same model · same promptsSee benchmark details →
Engineering principles<br>Built on first principles<br>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<br>Hundreds of agent replicas can't each cost gigabytes. Every byte per instance matters at scale — so we maintain a tight, tiny core.
Reliable<br>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<br>Declarative intent, automatic reconciliation. Individual agents are expendable; the organism persists.
Minimal cognitive load<br>Fewer concepts to learn, fewer knobs to turn. If a feature needs a paragraph of explanation, it's probably too complex.
WHAT'S NEW
Aug 4, 2026How Much Does the Agent Harness Matter?
Jul 25, 2026Claude Code Cut Their System Prompt by 80%. Does That Work for Small Models Too?
Apr 24, 2026From Arcade to Living Room: Offline Coding Models Hit Their Console Moment
Mar 31, 2026Introduce Ante: Self-Contained Agent That Self-Organize
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