Instead of signing up separately for GLM, Gemma, Nemotron, Qwen, and a dozen others, you manage everything in one place with automatic fallback if a provider goes down. This guide covers the best free models, how to call them in Python, how to wire OpenRouter into OpenClaw for a free agent, and when going direct beats it.

Best Free Models

OpenRouter marks free models with the :free suffix — no per-token cost, but they carry rate limits:

Free-model limits are account-wide, quoted from OpenRouter's docs: 20 requests/minute, and 50 requests/day until your account has bought $10 of credits at some point — after that, 1,000/day. Filter for all of them at openrouter.ai/models (":free"). To get a key: sign in at openrouter.ai with Google/GitHub/email, go to Keys, click Create Key. No credit card needed — you only add credits for paid models.

Using the API with Python

OpenRouter is fully OpenAI-compatible — just change base_url and api_key:

from openai import OpenAI

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

response = client.chat.completions.create(
    model="z-ai/glm-5.2:free",
    messages=[
        {"role": "user", "content": "Explain the difference between REST and GraphQL"}
    ]
)

print(response.choices[0].message.content)

Swap models by changing one string. For production, add fallback so your app survives a provider outage:

response = client.chat.completions.create(
    model="z-ai/glm-5.2:free",
    messages=[{"role": "user", "content": "Summarize the key features of Python 3.12"}],
    extra_body={
        "route": "fallback",
        "models": [
            "z-ai/glm-5.2:free",
            "nvidia/nemotron-3-super-120b-a12b:free",
            "google/gemma-4-31b-it:free"
        ]
    }
)

print(response.choices[0].message.content)
print(f"Model used: {response.model}")

Streaming works the same way:

stream = client.chat.completions.create(
    model="z-ai/glm-5.2:free",
    messages=[{"role": "user", "content": "Solve: What is 17 multiplied by 43, step by step"}],
    stream=True
)

for chunk in stream:
    if chunk.choices[0].delta.content:
        print(chunk.choices[0].delta.content, end="", flush=True)

Connect OpenRouter to OpenClaw (Free AI Agent)

Pair OpenRouter's free models with OpenClaw to build a free agent that uses tools and browses the web — switching models without code changes. Run npm install -g openclaw@latest && openclaw onboard, choose OpenAI-compatible, and enter the OpenRouter base URL and key. Or edit ~/.openclaw/openclaw.json:

{
  "models": {
    "mode": "merge",
    "providers": {
      "openrouter": {
        "baseUrl": "https://openrouter.ai/api/v1",
        "apiKey": "YOUR_OPENROUTER_API_KEY",
        "api": "openai-completions",
        "models": [
          {
            "id": "z-ai/glm-5.2:free",
            "name": "GLM 5.2 (Free)",
            "reasoning": true,
            "input": ["text"],
            "contextWindow": 256000,
            "maxTokens": 8192
          },
          {
            "id": "nvidia/nemotron-3-super-120b-a12b:free",
            "name": "Nemotron 3 Super (Free)",
            "reasoning": false,
            "input": ["text"],
            "contextWindow": 262144,
            "maxTokens": 8192
          },
          {
            "id": "google/gemma-4-31b-it:free",
            "name": "Gemma 4 31B (Free)",
            "reasoning": false,
            "input": ["text"],
            "contextWindow": 262144,
            "maxTokens": 8192
          }
        ]
      }
    }
  },
  "agents": {
    "defaults": {
      "model": {
        "primary": "openrouter/z-ai/glm-5.2:free"
      }
    }
  }
}

Now the agent can use GLM 5.2 for reasoning-heavy work, Nemotron for general tasks, and Gemma for quick light calls — all free.

OpenRouter vs Going Direct

We tested the "proxy overhead" assumption — it was wrong

The obvious objection to any router is that the extra hop costs you latency. So we measured it, twice, on the fairest possible comparison: the identical model, nemotron-3-super-120b, on OpenRouter's free tier and on NVIDIA's own first-party endpoint, same machine, same prompt.

OpenRouter was faster on both measures — and in an earlier run NVIDIA's endpoint returned an empty response for the same request while OpenRouter served it fine. Free capacity is shared and unevenly provisioned, so a router with spare headroom can beat the source. Measured 2026-08-31 with our open benchmark; see the full cross-platform results.

This doesn't make routing free in general — it means you should measure your specific model on both routes rather than assuming the vendor's own endpoint wins.

Verdict: OpenRouter wins for prototyping, research, and multi-model apps. For high-traffic production on a single model, direct is slightly better — lower latency and higher per-model limits.

OpenRouter vs Other Free AI APIs

Handling Rate Limits

Free models share limits across all users, so peak-time throttling is common. Loop through fallbacks on a RateLimitError:

import time
from openai import OpenAI, RateLimitError

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

FREE_MODELS = [
    "z-ai/glm-5.2:free",
    "nvidia/nemotron-3-super-120b-a12b:free",
    "google/gemma-4-31b-it:free"
]

def chat_with_fallback(prompt, models=FREE_MODELS):
    for model in models:
        try:
            response = client.chat.completions.create(
                model=model,
                messages=[{"role": "user", "content": prompt}]
            )
            return response.choices[0].message.content, model
        except RateLimitError:
            print(f"{model} rate limited, trying next...")
            time.sleep(1)
    return None, None

answer, used_model = chat_with_fallback("Explain async/await in Python")
print(f"Answer from {used_model}:n{answer}")

Frequently Asked Questions

Are OpenRouter's free models really free?

Yes — models with the :free suffix cost $0 per token with no credit card required. The only limit is rate, and it's account-wide: 20 requests/minute and 50 requests/day, rising to 1,000/day once your account has ever bought $10 of credits.

Do I need a credit card?

No. An email sign-up is enough to use every free model. You only add credits if you want to call paid models.

Is OpenRouter OpenAI-compatible?

Yes. It drops into existing OpenAI code — change only base_url to https://openrouter.ai/api/v1 and your api_key. The SDK, streaming, and message format are unchanged.

When should I go direct instead?

For high-traffic production on a single model, going direct to the provider gives lower latency and often higher per-model rate limits. OpenRouter wins for prototyping, benchmarking, and multi-model or fallback-dependent apps.

Final Thoughts

OpenRouter is the best choice when you want multiple AI models without juggling keys and endpoints. With around 18 genuinely free models — GLM 5.2, Nemotron 3 up to 550B, Gemma 4 — you get frontier-class AI at zero cost. The trade-offs are slightly lower per-model rate limits and a small routing latency, which are well worth it for building, testing, and prototyping. Get started: openrouter.ai — sign up free, grab your key, and explore 400+ models in minutes.