Cerebras vs Groq — The Fastest AI Inference Providers Compared

For chat, anything faster than reading speed is fast enough. For agents that generate thousands of tokens of plans and code, and for reasoning models that think at length before answering, a ten-times speed difference is the difference between a product that feels instant and one that feels broken. That is the market Cerebras and Groq serve.

Speed

Both are far faster than GPU-based providers; the published numbers run into the hundreds and, for smaller models, thousands of output tokens per second. Cerebras generally posts the higher figures on the models both offer, and its architecture keeps whole models in on-chip memory, which is why. Independent benchmark sites measure both and the lead changes by model and month, so check the current numbers for the model you plan to use rather than trusting either vendor's headline.

Models and ecosystem

Groq hosts a broader list, including speech models and more mid-sized options, and its free tier has seeded a large community of developers and tutorials. Cerebras hosts fewer models, focusing on the most popular open weights, and offers dedicated enterprise capacity for organisations that need guaranteed throughput.

Pricing and limits

• Both: free developer tiers with daily token or request limits, then pay per million tokens at rates competitive with GPU providers
• Free tiers queue under load; production use needs a paid plan on either
• Neither offers fine-tuning or custom model hosting for most customers; if you need your own weights served fast, ask about enterprise plans

Bottom line

If your model is on both, Cerebras is usually faster and Groq usually has more around it. If only one hosts your model, that decides it. Either way, for agentic and reasoning workloads on open models, switching from a GPU provider to one of these is the single biggest latency win available.