Cerebras — Fastest LLM Inference for AI Agents

What it is

Cerebras is a cloud inference service that runs large language models at extremely high speed. It delivers over 2000 tokens per second for models like Llama 3.3 70B and Qwen, using custom wafer-scale hardware designed specifically for AI workloads.

Cerebras targets AI developers and agent builders who need low-latency LLM responses for interactive applications, real-time agents, and batch processing workloads where inference speed is the bottleneck.

How it saves time or tokens

Cerebras inference is orders of magnitude faster than standard GPU-based providers. A response that takes 10 seconds on typical infrastructure completes in under 1 second on Cerebras. For agentic workflows with multiple LLM calls per task, this speed difference compounds significantly. Token estimate for this workflow is approximately 3400 tokens.

How to use

1. Install the Cerebras SDK:

pip install cerebras-cloud-sdk

1. Use the Cerebras client with your API key:

from cerebras.cloud.sdk import Cerebras

client = Cerebras(api_key='...')
response = client.chat.completions.create(
    model='llama-3.3-70b',
    messages=[{'role': 'user', 'content': 'Explain quantum computing'}],
)
print(response.choices[0].message.content)

1. Or use the OpenAI SDK with the Cerebras base URL:

from openai import OpenAI

client = OpenAI(
    base_url='https://api.cerebras.ai/v1',
    api_key='...',
)

Example

# Batch inference with Cerebras for agent workflows
from cerebras.cloud.sdk import Cerebras

client = Cerebras(api_key='your-key')

prompts = [
    'Summarize this document in 3 bullet points',
    'Extract all named entities from this text',
    'Generate a SQL query for this natural language request',
]

for prompt in prompts:
    response = client.chat.completions.create(
        model='llama-3.3-70b',
        messages=[{'role': 'user', 'content': prompt}],
    )
    print(response.choices[0].message.content)

Related on TokRepo

• AI Tools for Agents -- Agent frameworks that benefit from fast inference
• AI Gateway Solutions -- Compare inference providers and API gateways

Common pitfalls

• Cerebras supports a limited set of models (primarily Llama and Qwen families). Check model availability before building around a specific model.
• The OpenAI-compatible API covers chat completions but may not support all OpenAI-specific features like function calling or structured outputs.
• Pricing is usage-based. While inference is fast, high-volume batch jobs can accumulate costs quickly.