What is GoModel?
GoModel is a single-binary AI gateway in Go with caching, cost tracking and a dashboard. It sits in the Gateways & Routing category of the Evaluation & Production Ops tools and is open-source, written in Go and licensed MIT. To get started: install and start the gateway.
Overview
GoModel is an open-source AI gateway written in Go by ENTERPILOT. It sits between your application and the model providers you use, exposing two compatible surfaces — an OpenAI-compatible API at `/v1` and an Anthropic-compatible API at `/v1/messages` — so the official OpenAI and Anthropic SDKs work unchanged once you point their base URL at the gateway.
Behind that endpoint it fans out to a long list of providers: OpenAI, Anthropic, xAI, Google Gemini, Cohere, Vertex AI, DeepSeek, Groq, Fireworks AI, OpenRouter, Z.ai, Alibaba Cloud Model Studio, MiniMax, Azure OpenAI, Oracle, Amazon Bedrock, ElevenLabs, self-hosted runtimes such as Ollama, SGLang, vLLM and llm-d, and any other OpenAI-compatible endpoint. The project positions itself as an alternative to LiteLLM and Portkey and publishes self-reproducible benchmarks for its throughput and resource use.
The gateway is also where GoModel does the cross-cutting work you would otherwise scatter through application code: exact and semantic response caching so repeated prompts cost nothing, per-request cost estimates and spending breakdowns, budgets, prompt compression and intelligent routing. An admin dashboard at `/admin/dashboard` surfaces usage analytics and observability, and configuration resolves through built-in defaults, then `config.yaml`, then `.env`, then exported environment variables.
What it does
- One endpoint in two dialects — OpenAI-compatible at `/v1` and Anthropic-compatible at `/v1/messages` — so official SDKs work by changing only the base URL
- 25+ providers behind that endpoint, including hosted APIs, cloud platforms and local runtimes such as Ollama, vLLM and SGLang
- Exact and semantic response caching, so repeated prompts are served without a provider call
- Cost tracking with per-request estimates, usage analytics and spending breakdowns, plus hard budgets
- Admin dashboard for observability, token and cost monitoring, and the most important settings
- Ships as a single Go binary with an install script for macOS, Linux and Windows, plus a Docker image and Compose stack
Getting started
GoModel installs as one binary and starts with no configuration; provider keys are optional at first run and can be added later from the dashboard, a `.env` file or `config.yaml`.
Install and start the gateway
On macOS or Linux, run the install script and launch it. A PowerShell installer is available for Windows.
curl -fsSL https://gomodel.enterpilot.io/install.sh | sh
# OPENAI_API_KEY="your-openai-key" # optional
gomodelOr run it in Docker
The published image exposes the gateway on port 8080.
docker run --rm -p 8080:8080 \
-e OPENAI_API_KEY="your-openai-key" \
enterpilot/gomodelOpen the dashboard
Usage analytics, cost tracking and the main settings live in the admin UI.
http://localhost:8080/admin/dashboardSend a request through it
Call the OpenAI-compatible endpoint directly, or point an official SDK at http://localhost:8080/v1 (OpenAI) or http://localhost:8080 (Anthropic, which appends /v1/messages itself).
curl http://localhost:8080/v1/responses \
-H "Content-Type: application/json" \
-d '{
"model": "gpt-5-chat-latest",
"input": "Hello!"
}'Commands and code are distilled from the project's own documentation — always check the official repo for the latest.
When to use it
- Put one OpenAI- and Anthropic-compatible endpoint in front of every provider your team uses, so application code stops caring which one is behind it
- Cut spend on repeated prompts with exact and semantic caching, and see where the rest of the budget goes per request
- Enforce hard budgets and watch token usage across teams from a single dashboard
- Mix hosted APIs with self-hosted vLLM, SGLang or Ollama endpoints behind the same interface
How GoModel compares
GoModel alongside other open-source gateways & routing tools AI/TLDR tracks, ranked by GitHub stars.
| Tool | Stars | What it does |
|---|---|---|
| OmniRoute | ★ 83.9k | A local-first AI gateway that fronts hundreds of model providers with one OpenAI-compatible endpoint, quota-aware auto-fallback, many routing strategies and prompt compression. |
| Free Claude Code | ★ 65.9k | A local proxy that points Claude Code, Codex, Pi, OpenCode, Cline and other agent CLIs at 50 free, paid, subscription or local model providers, with automatic failover and an admin UI. |
| LiteLLM | ★ 62.6k | A Python SDK and proxy server that gives one OpenAI-compatible API to 100+ LLM providers, with cost tracking, budgets, fallbacks, rate limiting, and an admin UI. |
| Kong Gateway | ★ 44.3k | A Lua/NGINX API gateway whose AI Gateway plugins put one universal endpoint in front of OpenAI, Anthropic, Gemini, Bedrock and other providers, with semantic routing, caching and MCP traffic governance. |
| 9Router | ★ 31.9k | Local OpenAI-compatible router for coding CLIs that tracks per-provider quota, falls back from subscription to cheap to free models, and compresses tool results to cut tokens. |
| magpie | ★ 28.4k | Menu bar app and local gateway that lets Claude Code, Codex, Gemini CLI and dozens of other coding agents run on any provider's model, with routing groups that fail over across accounts when a quota runs out. |
| OpenCodex | ★ 18.2k | Local proxy that translates the Codex Responses API to 40+ providers, so Codex CLI, Claude Code and Grok Build can run on any model, with routing combos, failover and account pooling. |
| GoModel | ★ 1.3k | A single-binary AI gateway in Go with caching, cost tracking and a dashboard |
