FreeLLM vs OpenRouter

Both aggregate multiple LLM providers behind one OpenAI-compatible API. The key difference is where your keys and data live. OpenRouter is a managed cloud service that proxies your requests through their infrastructure. FreeLLM runs on your own infra, so your prompts and API keys never leave your servers.

Side-by-side comparison

When to use OpenRouter instead

OpenRouter is the better choice in these situations:

• You need paid models like GPT-4o, Claude 3.5 Sonnet, or Gemini Ultra. FreeLLM only covers free tiers.
• You do not want to manage infrastructure. OpenRouter is fully managed and requires no deploy step.
• You need access to providers beyond the 8 free-tier ones FreeLLM ships with.
• You are fine with your prompts transiting OpenRouter's servers.

When FreeLLM makes sense

FreeLLM fits better when any of these apply:

• You want your prompts and API keys to stay on servers you control. Useful when working with sensitive data or internal tooling.
• You need zero recurring cost. No credits, no per-token markup, no surprise bills.
• You are building something where data residency matters, such as internal enterprise tools or regulated industries.
• You want circuit breakers, response caching (~23ms cache hits), and virtual sub-keys without building them yourself.

The code change is two lines

If you are already on OpenRouter, switching to FreeLLM is a base URL and key swap. The rest of your code stays the same.

from openai import OpenAI

client = OpenAI(
    base_url="https://openrouter.ai/api/v1",
    api_key="sk-or-..."
)

from openai import OpenAI

client = OpenAI(
    base_url="https://your-freellm-instance/v1",  # your own server
    api_key="your-freellm-key"
)