Keywords AI

Cerebras vs Groq

Compare Cerebras and Groq side by side. Both are tools in the Inference & Compute category.

Quick Comparison

	Cerebras	Groq
Category	Inference & Compute	Inference & Compute
Pricing	Usage-based	Freemium
Best For	Enterprises and developers who need the fastest possible LLM inference	Developers building real-time AI applications where inference speed is the top priority
Website	cerebras.net	groq.com
Key Features	Wafer-scale inference chips Record-breaking inference speed Simple API deployment Optimized for large language models Custom silicon architecture	Custom LPU inference chips Ultra-low latency inference Fastest tokens-per-second performance OpenAI-compatible API Free tier for experimentation
Use Cases	Ultra-fast LLM inference Real-time AI applications High-throughput text generation Enterprise inference infrastructure Latency-critical AI deployments	Real-time AI applications needing lowest latency Interactive conversational AI High-throughput batch inference Cost-efficient inference for open-source models Latency-sensitive production deployments

When to Choose Cerebras vs Groq

Choose Cerebras if you need

Ultra-fast LLM inference
Real-time AI applications
High-throughput text generation

Pricing: Usage-based

Choose Groq if you need

Real-time AI applications needing lowest latency
Interactive conversational AI
High-throughput batch inference

Pricing: Freemium

About Cerebras

Cerebras builds the world's largest AI chips—wafer-scale processors that contain millions of cores on a single silicon wafer. The Cerebras CS-2 system delivers massive parallelism for AI training and ultra-fast inference for open-source models. Through Cerebras Inference, developers can access some of the fastest LLM inference speeds available, particularly for Llama models.

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About Groq

Groq builds custom AI inference chips (Language Processing Units / LPUs) designed for extremely fast token generation. Groq's cloud platform offers the fastest inference speeds in the market, generating hundreds of tokens per second for models like Llama and Mixtral. The company's hardware architecture eliminates the memory bandwidth bottleneck that limits GPU-based inference, making it ideal for real-time and latency-sensitive AI applications.

View Groq profile →Visit website

What is Inference & Compute?

Platforms that provide GPU compute, model hosting, and inference APIs. These companies serve open-source and third-party models, offer optimized inference engines, and provide cloud GPU infrastructure for AI workloads.

Browse all Inference & Compute tools →