OpenRouter Alternatives 2026: 6 Open Source LLM Gateways Compared With Real Stars

๐Ÿ”ง AI Tools 2026-08-13 2 min read

OpenRouter is convenient until you want control over routing, cost or data. These six open source gateways give you the same one-API experience on your own infrastructure.

💡 What You Will Learn

OpenRouter is convenient until you want control over routing, cost or data. These six open source gateways give you the same one-API experience on your own infrastructure.

📜 Table of Contents

Why Teams Leave OpenRouter

OpenRouter's value is a single API in front of hundreds of models. Its limits are equally clear: you pay their margin, your prompts transit their servers, and you cannot enforce per-team budgets or custom routing. The open source answer is the LLM gateway - a self-hosted proxy that speaks OpenAI's API on one side and talks to any provider on the other. Stars fetched 2026-08-13.

The Gateways

LiteLLM (56,191 stars) - the default choice. One Python library and proxy covering 100+ providers with a unified format: OpenAI-compatible, Anthropic-compatible, and hundreds of open models via their providers. Handles key management, fallbacks, retries, and simple load balancing. The fastest path from OpenRouter to self-hosted.

one-api (36,345 stars) - the Chinese ecosystem favorite. A management panel with user/group/token billing, model pricing overrides, and quota limits - built for teams that resell or meter API access internally.

new-api (45,005 stars) - a maintained fork of one-api with more provider integrations and a cleaner dashboard. If one-api's maintenance cadence worries you, this is the modern branch.

Portkey AI Gateway (12,702 stars) - the enterprise-leaning option: guardrails, caching, observability, and routing rules built into the proxy. Heavier to run, but it replaces a whole middleware stack.

The Decision Table

Need Pick
Fastest migration from OpenRouter LiteLLM
Per-user quotas and billing one-api / new-api
Guardrails + caching + routing in one Portkey
Multi-provider fallback LiteLLM

Migration in One Line

With LiteLLM, existing OpenAI code keeps working - change base_url and api_key, nothing else:

from openai import OpenAI
client = OpenAI(base_url="http://localhost:4000", api_key="your-key")

The 2026 Pattern

The typical self-hosted stack: LiteLLM as the proxy in front of mixed providers (a frontier API for hard tasks, a cheap open model for easy ones), one-api/new-api where internal billing matters, and Portkey when the app needs guardrails and caching without extra services. All four are open source - the traffic, keys and cost data stay in your network.

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