Quickstart

Make your first Cerebras API call in just minutes.

Get started with the world’s fastest inference. Already familiar with LLM APIs? Skip straight to the API reference or try the playground.

Want to try it without setup? Use the playground in the Cloud Console — no key or install needed. Come back for the code walkthrough below.

1. Set up your API key

   Visit the Cloud Console and sign up or log in. Navigate to API Keys in the left nav bar to create a key. See API Keys for details.

   Set your API key as an environment variable so you don’t have to pass it with every request:

   macOS / Linux

   export CEREBRAS_API_KEY="your-api-key-here"
   

   Confirm the variable is set:

   macOS / Linux

   echo $CEREBRAS_API_KEY
   

   export and $env: set the variable for the current shell only. setx on Windows persists the variable, but you must open a new terminal window for it to take effect. To persist on macOS or Linux, add the export line to your ~/.zshrc, ~/.bashrc, or equivalent shell profile.

2. Install the SDK

   Install the Cerebras SDK for your language of choice. You can also call the API directly with cURL (see Step 3).

   Python

   pip install --upgrade cerebras_cloud_sdk
   
3. Make your first API request

   Run the following code to send a chat completion request. The examples use gpt-oss-120b; see the model catalog for other options.

   Python

   import os
   from cerebras.cloud.sdk import Cerebras
   
   client = Cerebras(
       api_key=os.environ.get("CEREBRAS_API_KEY"),
   )
   
   chat_completion = client.chat.completions.create(
       messages=[
           {
               "role": "user",
               "content": "Why is fast inference important?",
           }
       ],
       model="gpt-oss-120b",
   )
   
   print(chat_completion.choices[0].message.content)
   

   You should see a response like:

   Fast inference is important because it enables real-time interactions,
   reduces latency in production applications, and allows for more complex
   reasoning workflows within acceptable response times...
   

Common Errors

• 401 Unauthorized — CEREBRAS_API_KEY isn’t set in the shell running your code. Re-run the echo command above in the same terminal to confirm. On Windows after setx, open a new terminal.
• 404 model not found — The model ID is misspelled, deprecated, or not available on your account. See the full list of public models on the Models page.
• 429 Too Many Requests — You’ve hit a rate limit. Free accounts have lower per-minute limits than paid accounts. See Rate limits for current quotas and how to request an increase.

For all status codes, see the error reference.

Next Steps

• Choose a model — Find the right model for your use case in our model selection guide.
• Explore capabilities — Add streaming, tool calling, structured outputs, or reasoning to your application.
• Design for Cerebras — Learn architectural patterns that take full advantage of wafer-scale inference.
• Browse the API — See all available endpoints and parameters in the API reference.