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Self-contained agents that self-organize

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.

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

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

01

Install in one command

One curl. A single 13 MB binary, checksum-verified. No account, no config file, no Node.

02

Pick a model

Switch between providers and models mid-session, and dial the effort from faster to smarter. Cloud or local.

03

Ask, and watch it ship

One sentence in, a working API out: scaffolded, rate-limited, tested. It runs the suite, fixes its own mistake, and finishes green.

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 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 →

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.