Founded by Andrew Feldman in 2016
Run high-speed artificial intelligence model inference and training on wafer-scale chips
Pricing model
Free Tier
Rating
★ People love it
Time to value
Quick Setup (< 1 hour)
You can use Cerebras to run large language models and deep learning models at ultra-fast speeds using specialized wafer-scale processors. The service allows you to replace standard GPU clusters for AI inference and training, delivering high throughput and low latency for generative AI applications. You can connect through an OpenAI-compatible API to instantly serve open-source or proprietary models. Developers can also fine-tune or pre-train custom models in the cloud or on-premise, making it easier to build real-time AI agents, voice assistants, and code completion tools.
What Cerebras does
Pricing breakdown
Pricing model: Free tier
Tutorials & Demos
Frequently asked
Want a tailored answer?
See whether Cerebras fits your stack.
Techbible weighs Cerebras against what you already pay for, your team shape, and the work that's actually happening. Free to start.
Side by side
Compare Cerebras
Search the catalog or pick a similar tool to compare pricing, features, and fit.
Or pick from similar tools
More in AI Hosting & Inference
All tools →Modal
Run serverless AI model training, inference, and batch jobs on cloud GPUs
Ollama
Run open large language models locally on your machine or in the cloud
.wave
Run continuous inference for real-time voice and streaming speech models
Baseten
Deploy and serve custom machine learning models with dedicated cloud infrastructure
Cerebrium
Deploy and scale machine learning models on serverless GPUs with pay-per-second pricing
Clockwork Systems, Inc.
Keep distributed machine learning workloads running through GPU and network hardware failures
CloudRift
Manage and virtualize private GPU clusters for enterprise model training and inference
CUDOS
Rent distributed cloud compute and GPU hardware for artificial intelligence and rendering workloads