Stacking free tiers by hand is painful — dozens of SDKs, dozens of rate limits, and no idea how much you actually have. OmniRoute aggregates the documented free tiers of 39 provider pools / 460+ models into one honest number and shows it live on the dashboard (/dashboard/free-tiers).
Animated summary of the live /dashboard/free-tiers page. Full methodology (pool dedupe, credit tiers, provider terms): docs/reference/FREE_TIERS.md.
These figures are re-audited every two weeks against the live catalog and move both ways — a provider ends a free tier and the number drops; a new one lands and it climbs. We publish what the catalog actually computes, never a rounded-up best case. A CI gate (check:docs-counts) fails the build if this headline drifts from the code.
⭐ Star the repo if OMNIROUTE helped you save money and make your work easier.
Questions, provider tips, roadmap & support → Discord · Telegram · WhatsApp 🌍 Global / 🇧🇷 Brasil
🚀 Quick Start • 🎯 Combos • 🌐 Providers • 🔌 CLI & MCP • 🗜️ Compression • 🌍 Website
💥 The Promise • 🤔 Why • 🏆 What Sets Apart • 🤖 Compatible CLIs • 🖥️ Where It Runs • 🔒 Private • 🎬 In Action • 📸 Screenshots • 📧 Support
A combo is a chain of models OmniRoute routes across automatically. Quota runs out, a provider fails, or costs spike — the combo silently slides to the next model. This is what makes OmniRoute unbreakable. 🛡️
No combo to create. Set your model to auto (or a variant) and OmniRoute builds a virtual combo from your connected providers, scored live:
All 18 strategies — mix & match per combo step:
The Auto-Combo engine scores every candidate on 12 factors (health, quota, cost, latency, success rate, freshness…) — see docs/routing/AUTO-COMBO.md.
Running several keys against the same upstream account (one Codex Pro plan, one Kimi key, one GLM Coding seat)? A burst on one key can burn the whole 5-hour / hourly quota and lock everyone else out. Quota-Share distributes a provider's time-based quota fairly across the keys in a pool — and it's work-conserving, so an idle member's slice is lent out instead of wasted.
Enforced in the hot path before the request leaves OmniRoute, with per-(key, model) caps + session stickiness for prompt-cache integrity (now with a per-combo / global disable toggle). 📖 Quota Sharing Engine
📊 Detailed comparison vs LiteLLM, OpenRouter & Portkey → docs/comparison/OMNIROUTE_VS_ALTERNATIVES.md
Recent highlights from v3.8.20 → v3.8.49. Full history in CHANGELOG.md.
One config — http://localhost:20128/v1 — and every AI IDE or CLI runs on free & low-cost models.
📖 Per-tool setup for all 33 tools (25 CLI Code's + 8 CLI Agents) → docs/reference/CLI-TOOLS.md · 🧩 OpenCode plugin → @omniroute/opencode-provider
The most complete catalog of any open-source router: 268 providers, 90+ with a free tier, 40+ free forever.
…and 220+ more — every icon resolves live from the dashboard's provider catalog. 📖 Provider Reference
📖 Full machine-readable catalog → docs/reference/PROVIDER_REFERENCE.md
Same app, your machine, your rules. From a global npm install to your phone via Termux.
📖 Docker Guide · Desktop · Termux · PWA · OpenCode
📖 Authorization · Guardrails · Compliance
OmniRoute isn't just a server — it's a full command-line cockpit with 80+ commands, plus open agent protocols so an AI agent can drive OmniRoute by itself.
OmniRoute on a server? Drive it from your laptop with the same CLI. Log in once with a scoped access token; every command then targets the remote.
Tokens are scoped read / write / admin; process-spawning routes stay loopback-only. 📖 Remote Mode
Expose OmniRoute over MCP or A2A and any capable agent gets the keys to the whole gateway — routing, providers, combos, cache, compression, memory — autonomously.
📖 MCP Server · A2A Server · Agent Protocols
Why use many tokens when few tokens do the trick? Every request passes through OmniRoute's compression pipeline transparently — no client changes. It's now a stack of 11 composable engines that run in order and mix & match per routing combo — building on ideas from RTK, Caveman (⭐ 90K+), LLMLingua-2, and Troglodita (PT-BR).
Engines run in pipeline order; each is independently toggleable and configurable per combo:
Code blocks, URLs and structured data are always preserved byte-perfect. One-click presets combine the engines:
Before (69 tokens): "The reason your React component is re-rendering is likely because you're creating a new object reference on each render cycle. When you pass an inline object as a prop, React's shallow comparison sees it as a different object every time, which triggers a re-render. I would recommend using useMemo to memoize the object."
After (19 tokens): "New object ref each render. Inline object prop = new ref = re-render. Wrap in useMemo."
Same answer. 72% fewer tokens. Zero accuracy loss. ✅
Antes (42 tokens): "O problema é que o componente está re-renderizando porque uma nova referência de objeto está sendo criada em cada ciclo de renderização. Eu recomendaria usar useMemo."
Depois (12 tokens): "Re-render: ref nova cada ciclo (objeto inline recriado). Usar useMemo."
Mesma resposta. ~70% menos tokens. Precisão técnica intacta. ✅
Default stacked combo runs RTK → Caveman. When both act on the same tool/context payload, savings compound:
Code blocks, URLs, JSON and structured data are always protected by the preservation engine.
The 10 engines above shrink what goes in. Three more layers shape how, when, and what comes out:
🪄 Output Styles (output-axis steering) — inject deterministic, cache-safe response-shaping instructions; combinable, each at lite / full / ultra intensity. Adding a style is a one-line registry entry: Terse prose — drop filler / articles / hedging; keep technical substance exact. Less code — "lazy senior dev" YAGNI: smallest working change, no unrequested scaffolding. Terse CJK (文言) — classical-Chinese ultra-terse style (locale-gated to zh).
Less code — "lazy senior dev" YAGNI: smallest working change, no unrequested scaffolding.
🎯 Adaptive context-budget (the dial) — instead of one on/off token threshold, escalate the cheapest, most-lossless engines only as far as needed to fit the model's context window. Policy: reserve-output (default, model-aware) · percentage · absolute. Mode: floor (guarantee fit) · replace-autotrigger (your explicit choice wins) · off (legacy threshold).
🎛️ Where compression is decided (precedence, high → low) — per-request x-omniroute-compression header › routing-combo override › active named profile › adaptive / auto-trigger › panel default › off. The applied plan echoes back in the X-OmniRoute-Compression: <mode>; source=<source> response header.
Auto-trigger by token threshold, flip on the adaptive dial, pin a named profile, set a one-off per request, or assign a pipeline per routing combo — whichever fits the workload. An opt-in offline eval harness (npm run eval:compression) scores fidelity vs. savings on a pinned corpus before you promote a change.
📖 COMPRESSION_GUIDE.md · RTK_COMPRESSION.md · COMPRESSION_ENGINES.md
Dashboard at http://localhost:20128 · API at http://localhost:20128/v1.
Dashboard → Providers → connect Kiro AI (free Claude, ~50 credits/month per account) or OpenCode Free (no auth) → done.
You should see your connected models listed. 🎉 That's it — start coding, and OmniRoute auto-routes & falls back for you.
If your client cannot send custom headers, OmniRoute also exposes tokenized compatibility aliases:
Use these only for clients that cannot attach Authorization: Bearer .... Header auth remains the preferred mode.
📖 Docker Guide — Compose profiles, Caddy HTTPS, Cloudflare tunnels.
📖 Podman Guide — Quadlet setup, podman-compose, Quadlet.
⚡ Faster / leaner install (skip the native build)
The native SQLite engine (better-sqlite3) is an optional dependency, so a global install never blocks on compiling from source: it uses a prebuilt binary when one matches your platform/Node, and otherwise falls back transparently to a pure-JS engine (node:sqlite on Node 22+, else the bundled sql.js WASM) — no build tools required.
To skip the post-install native warm-up entirely (CI, headless, or slow machines):
For the fastest installs prefer pnpm (content-addressed store + hard links — see above). For a dashboard-free, headless runtime use the Docker base profile (above) or the Termux guide. The CLI and the web dashboard are served by the same process on one port, so there is no separate CLI-only package today.
🎬 Made a video about OmniRoute? Open an issue or discussion with the link — we'll feature it here.
💬 Chat with the community — Discord, Telegram & WhatsApp (🌍 / 🇧🇷) links are at the top of this README.
OmniRoute is shaped by a passionate open-source community. These individuals have made exceptional contributions that directly impact the quality, stability, and reach of the project. Thank you.
🙏 These contributors' features, bug fixes, and infrastructure improvements are a core part of what makes OmniRoute reliable and feature-rich. Every pull request, every test case, and every i18n translation file matters. Open source is built by people like them.
See CONTRIBUTING.md for detailed guidelines.
OmniRoute stands on the shoulders of giants. It started as a fork of 9router and a TypeScript port of the Go project CLIProxyAPI — and from there, every subsystem below was inspired by an open-source project that got there first. Each one shaped a concrete piece of OmniRoute. This is our thank-you to all of them. 🙏
⭐ star counts as of July 2026 — go give these projects a star.
Want to appear here? OmniRoute puts sponsors in front of one of GitHub's fastest-growing AI-gateway communities — and we say publicly where every sponsored token goes. Reach out: diegosouza.pw@outlook.com
OmniRoute is free and open source, built and maintained in the open. If it saves you time or money, consider supporting development:
⬆ Back to top · Built with ❤️ for the open-source AI community.
OmniRoute v3.8.49 · Node ≥22.22.2 · MIT License · omniroute.online