GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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Decision brief
Atomic-Chat is a local AI app and inference engine for agents that runs open-weight LLMs privately offline.
Good fit when
- When you need to run large language models (LLMs) locally with full privacy and no internet connectivity required.
- Suitable if your work involves deep integration with Apple Silicon or requires specific support for self-hosted environments like Gemma and GGUF.
Avoid when
- Avoid Atomic-Chat when you need cloud-based AI services that offer automatic updates and maintenance, as it focuses on local offline deployment.
- Do not choose this tool if your project does not require deep-seek capabilities or self-hosted solutions but prefers more mainstream LLMs like Qwen.
- Hosting:
- self hosted
- Requirements:
- Atomic-Chat requires TypeScript for development.; Ensure you have the necessary hardware and setup to run open-weight LLM models locally.
Observed Jul 14, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Very active (0d since push)
- As of Sep 19, 2026
- Provenance
- Not a fork · Organization account
- As of Sep 19, 2026
- Security (OSV)
- No MCP manifest
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
npm install Atomic-ChatHow it fits your stack(1)
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Evidence and technical details
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Overview
A local AI application that allows users to run open-weight LLMs privately offline on their own computers.
Capability facts
- MCP server
- No MCP server detected
Source: repo_scan · Sep 19, 2026
- Languages
- typescript, javascript
Source: github.language+package.json · Sep 19, 2026
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README
💻 System Requirements macOS : 13.6+ (8GB RAM for 3B models, 16GB for 7B, 32GB for 13B) Windows : 10/11 x64 (same RAM recommendations as macOS) Linux : x86 64, glibc ≥ 2.35 (Ubuntu 22.04+, Debian 12+, Fedora 40+, Arch, Mint, Pop! OS — same RAM recommendations as macOS). Optional:...
For agents
This page has a .md twin and JSON over the API.