Atomic Chat

Atomic Chat

Local AI app and inference engine for agents. Run open-weight LLMs locally — private, on your machine.

Getting Started · Hugging Face · Discord · X / Twitter · Bug Reports

📦 Download

Desktop

Linux packages — from the Atomic Chat repository, updated by your package manager (how to install)

Mobile

🔌 Use It as an API

Atomic Chat runs an OpenAI-compatible server at http://localhost:1337/v1 — a drop-in replacement for the OpenAI SDK. Load a model in the app, then point any client at it:

curl http://localhost:1337/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "<model-id-loaded-in-atomic-chat>",
    "messages": [{ "role": "user", "content": "Say hello in one word" }]
  }'

from openai import OpenAI

# Atomic Chat is OpenAI API-compatible — only the base_url changes.
client = OpenAI(base_url="http://localhost:1337/v1", api_key="not-needed")

resp = client.chat.completions.create(
    model="<model-id-loaded-in-atomic-chat>",
    messages=[{"role": "user", "content": "Say hello in one word"}],
)
print(resp.choices[0].message.content)

Bound to 127.0.0.1 by default; set host: 0.0.0.0 to expose it on your LAN. Works with any agent, CLI, or IDE plugin that speaks the OpenAI API — see Launch With below.

✨ Features

Local models

• Run open-weight LLMs locally from HuggingFace — Llama, Gemma, Qwen, Mistral, Phi, and others
• Multi-Token Prediction (MTP) speculative decoding — 30–70% throughput boost on supported models, up to 3× on Gemma 4
• DFlash block-diffusion decoding — up to 6× faster on Qwen 3.6, Gemma 4, Kimi K2.5
• Flash Attention toggle (on / off / auto)
• Automatic reasoning-context tracking for chain-of-thought models
• Auto context-window expansion with overflow notifications
• EAGLE-3 speculative decoding for Gemma 4 on Apple Silicon (MLX)
• MTP on MLX for Qwen 3.5 / 3.6 and DeepSeek V4
• TurboQuant KV cache (turbo3 / turbo4) on llama.cpp — now on Windows & Linux too, not just macOS: up to ~4.3× smaller KV cache footprint, CPU and GPU (CUDA / Vulkan)
• TurboQuant KV cache on MLX-VLM — smaller memory footprint via RHT-correct fast paths

Cloud models

• Built-in providers: OpenAI, Anthropic, Mistral, Groq, MiniMax, Qwen, Moonshot
• Bring your own key, switch model per chat, mix local and cloud freely

Tools & integrations

• One-click agent launch — launch agents like Atomic Agent, Claude Code, Codex CLI, Cline, OpenCode, Droid, Goose, OpenHands, Copilot CLI, Kilo Code, Zed and ZCode in one click from the Integrations tab
• Artifacts — live preview panel for HTML/CSS/JS code with copy, download and print
• Connect multiple MCP servers — bring your own tools, file access, web search
• Custom assistants with per-assistant system prompts
• Projects with conversation tree view in the sidebar

Local API

• OpenAI-compatible server at http://localhost:1337/v1 — drop-in replacement for the OpenAI SDK
• Works with any agent, CLI, or IDE plugin that speaks the OpenAI API
• Bound to 127.0.0.1 by default; set host: 0.0.0.0 to expose on LAN

Privacy

• Everything runs locally when you want it to — local server is loopback-only by default
• Your conversations and keys stay on your machine

⚙️ Inference Engines

Three engines under the hood, all exposed through one OpenAI-compatible API at http://localhost:1337/v1:

• atomic-llama-cpp-turboquant — our llama.cpp fork with TurboQuant KV-cache optimizations (turbo3 / turbo4) for faster, lower-memory quantized inference. Now a selectable second provider ("Atomic Llama.cpp Turboquant") on all three desktops — macOS, Windows, and Linux — CPU and GPU (CUDA / Vulkan).
• Upstream llama.cpp — official ggml-org build, the default engine on Windows and Linux for the widest hardware coverage and MTP support.
• MLX-VLM — Apple Silicon-native engine for vision-language models, running on the Neural Engine and unified memory. Faster than llama.cpp on M-series chips for supported models.

Speculative-decoding features available across backends:

• MTP (Multi-Token Prediction) — a draft model predicts ahead, the full model verifies in one pass. Available on macOS and Windows.
• DFlash — block-diffusion speculative decoding for Qwen 3.6, Gemma 4, Kimi K2.5 and others. Apple Silicon only; can't be enabled together with MTP.
• Flash Attention — Settings → on / off / auto.

Tools talking to http://localhost:1337/v1 don't need to know which backend is running underneath — switch engines without reconfiguring clients.

The engines are driven by atomic-chat-core — the core of Atomic Chat, in its own repository. It doesn't do inference itself; it manages the engines: downloads and launches backends, manages models, routes requests between local engines and cloud providers, and serves the OpenAI-compatible API on :1337. The desktop app ships a pinned core release; the core also runs on its own as a CLI (atomic-chat-core serve …) or as a library.

🚀 Launch With

Atomic Chat runs an OpenAI-compatible server at http://localhost:1337/v1, so any agent, CLI, IDE plugin, or app that speaks the OpenAI API can run on top of your local models — no extra glue needed. Just point its base URL at Atomic Chat and you're done.

A few projects already ship first-class support with their own setup docs:

Built something that runs on Atomic Chat? Open a PR and we'll add it here.

🛠️ Build from Source

Prerequisites

• Node.js ≥ 20.0.0
• Yarn ≥ 4.5.3
• Make ≥ 3.81
• Rust (for Tauri)
• (Apple Silicon) MetalToolchain xcodebuild -downloadComponent MetalToolchain

Run with Make

git clone https://github.com/AtomicBot-ai/Atomic-Chat
cd Atomic-Chat
make dev

This handles everything: installs dependencies, builds core components, and launches the app.

Available make targets:

• make dev — full development setup and launch
• make build — production build
• make test — run tests and linting
• make clean — delete everything and start fresh

Manual Commands

yarn install
yarn build:tauri:plugin:api
yarn build:core
yarn build:extensions
yarn dev

💻 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: a Vulkan loader (vulkan-1 package, or mesa-vulkan-drivers / proprietary NVIDIA driver) for GPU acceleration.
• iOS: download from App Store
• Android: download from Google Play

🐧 Running on Linux

Install it from the Atomic Chat package repository, and your package manager updates it with the rest of the system. The packages put the app in /opt/atomic-chat with an atomic-chat command, a menu entry, and the system's WebKitGTK; the built-in updater stays off. On arm64 they need glibc 2.38 or newer, which the bundled llama.cpp engine is built against there. The repository and the rpm packages are signed with the Atomic Chat packages key in packaging/atomic-chat.asc, fingerprint 1047 F119 58C6 442D D472 E497 E4C3 D361 FB7F F123.

Debian, Ubuntu — Debian 12+ / Ubuntu 22.04+ on x86-64, Debian 13+ / Ubuntu 24.04+ on arm64:

curl -fsSL https://atomic-chat-packages.fsn1.your-objectstorage.com/atomic-chat.gpg | sudo tee /usr/share/keyrings/atomic-chat-app.gpg >/dev/null
echo "deb [signed-by=/usr/share/keyrings/atomic-chat-app.gpg] https://atomic-chat-packages.fsn1.your-objectstorage.com/deb stable main" \
  | sudo tee /etc/apt/sources.list.d/atomic-chat-app.list
sudo apt update && sudo apt install atomic-chat

Fedora 40+ (x86-64, aarch64):

sudo curl -fsSL -o /etc/yum.repos.d/atomic-chat-app.repo https://atomic-chat-packages.fsn1.your-objectstorage.com/rpm/atomic-chat.repo
sudo dnf install atomic-chat

Arch Linux (x86-64, aarch64): yay -S atomic-chat-bin, or any other AUR helper.

Then start Atomic Chat from the app menu, or run atomic-chat.

Updates come with sudo apt upgrade, sudo dnf upgrade or yay -Syu. sudo apt remove atomic-chat, sudo dnf remove atomic-chat or sudo pacman -R atomic-chat-bin removes the app and leaves your chats and models. The repository keeps the last three releases; every release also carries its .deb and .rpm files on the releases page.

Or run the self-contained .AppImage — no installer, no root, and it updates itself:

chmod +x Atomic.Chat_*_amd64.AppImage
./Atomic.Chat_*_amd64.AppImage

If prompted about FUSE on first launch: sudo apt install fuse libfuse2 (Debian/Ubuntu) or sudo dnf install fuse fuse-libs (Fedora). GPU acceleration (Vulkan) is auto-detected on first launch; only GGUF models run on Linux.

When your bar has a tray (Omarchy, Waybar's tray module, KDE), closing the window keeps Atomic Chat and its local API on :1337 running in the tray; use Quit in the tray menu to stop it. Launching the app again brings the window back. Without a tray (GNOME with no indicator extension), closing the window quits as usual.

Window rules (Hyprland, Sway). Match the Wayland app id (Hyprland class) chat.atomic.app, e.g. ^chat\.atomic\.app$. Under X11/XWayland the window class is still Atomic-Chat.

Packaging. A distro package (AUR, a pacman repo, Flatpak) that owns updates should place an empty atomic-chat-package-managed file next to the .AppImage (or, for an extracted AppImage, next to usr/bin/Atomic-Chat), or start the app with ATOMIC_CHAT_PACKAGE_MANAGED=1. Prefer the file: the "launch at startup" entry runs the AppImage or binary directly, so it does not see a variable set in a launcher script. The built-in updater then never checks for, offers or installs updates, and Settings points users to their package manager.

🧯 Troubleshooting

If something isn't working:

1. Copy your error logs and system specs
2. Open an issue on GitHub
3. Or ask for help in our Discord

👥 Contributors

Atomic Chat is built by a small core team and 140+ contributors — including everyone who shaped the project from its earliest days. Pull requests are welcome in both repositories:

• Atomic-Chat (this repo) — the desktop and mobile app: UI, chats, assistants, projects, MCP, integrations, settings. See CONTRIBUTING.md to get started.
• atomic-chat-core — the core that manages the engines (llama.cpp, MLX, Foundation Models): backend and model management, cloud providers, the router and the OpenAI-compatible server. See its AGENTS.md to get started.

Not sure where a change belongs? Open an issue in either repo and we'll point you the right way.

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