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Cerebras

Wafer-scale AI chips powering ultra-fast inference cloud and on-prem deployment.

Last updated: Jul 31, 2026

About Cerebras

Cerebras Systems, founded in 2015 and based in Sunnyvale, California, builds specialized hardware for AI computation, centered on its Wafer-Scale Engine (CS-3) chip. The company describes the chip as dramatically larger than a standard GPU die, a design choice that lets it hold entire model weights on-chip in SRAM rather than shuttling them across networked GPUs, which the company says translates into markedly faster inference. On top of that hardware, Cerebras runs an Inference Cloud service offering hosted access to open models such as Llama, Qwen, and GLM through an API. The API is built to be a drop-in replacement for the OpenAI Chat Completions API, so existing applications can switch providers with minimal code changes. Cerebras reports throughput figures in the thousands of tokens per second on supported models, and offers three deployment modes: a hosted cloud, dedicated infrastructure for a single customer, and fully on-premise systems for organizations with data residency requirements. The company has attracted partnerships with major AI players, including OpenAI, AWS, and Meta, and recently announced work with AMD combining Cerebras's fast token generation with AMD's prefill capacity. Cerebras targets developers and enterprises that need low-latency inference at scale rather than training-only workloads.

At a glance

Company
Cerebras Systems (est. 2015)
Platforms
Web, API
API
Available
Last verified
July 2026

♥Bookmarked by 1 person on Aigregator.

Last updated: July 31, 2026

Who It's For

  • •AI researchers
  • •Large enterprise data centers
  • •Supercomputing facilities
  • •AI hardware engineers

How It Works

  1. 1Uses wafer-scale chips to process AI workloads at unprecedented speeds.
  2. 2Stores all model weights in on-chip SRAM for rapid access and reduced latency.
  3. 3Optimizes AI inference performance, enabling instant responses.
  4. 4Focuses on large-scale AI model training and inference acceleration.

How to Use Cerebras

  1. 1Deploy the Cerebras hardware in data centers or AI research facilities.
  2. 2Integrate their chips with existing AI frameworks via supported APIs and SDKs.
  3. 3Configure models for inference or training on Cerebras hardware to leverage its speed.
  4. 4Utilize their platform for deploying large AI models with high efficiency.

Key Features

  • •Wafer-Scale Engine (CS-3) chip
  • •Inference Cloud API
  • •OpenAI API compatibility
  • •Cloud, dedicated, and on-premise deployment

Use Cases

  • •Running low-latency LLM inference at scale
  • •Migrating OpenAI API workloads to faster inference
  • •On-premise AI deployment for data residency compliance

Pros & Cons

Advantages

  • •Revolutionary wafer-scale chip design offers unmatched speed.
  • •Enables large-scale AI models to run efficiently.
  • •Holds world records in AI inference performance.

Disadvantages

  • •Highly specialized hardware may be costly and complex to implement.
  • •Limited to high-end AI applications and enterprises.
  • •Less flexibility compared to GPU-based solutions.

Alternatives

  • Groq
  • NVIDIA
  • SambaNova

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Frequently Asked Questions

What is Cerebras?

Cerebras Systems, founded in 2015 and based in Sunnyvale, California, builds specialized hardware for AI computation, centered on its Wafer-Scale Engine (CS-3) chip. The company describes the chip as dramatically larger than a standard GPU die, a design choice that lets it hold entire model weights on-chip in SRAM rather than shuttling them across networked GPUs, which the company says translates into markedly faster inference.

How much does Cerebras cost?

Cerebras uses custom pricing — contact the vendor for a quote.

Is Cerebras free?

Cerebras is a paid tool and does not offer a free plan.

What are the best Cerebras alternatives?

Popular Cerebras alternatives include Groq, NVIDIA, SambaNova.

What is Cerebras used for?

Cerebras is commonly used for Running low-latency LLM inference at scale, Migrating OpenAI API workloads to faster inference, On-premise AI deployment for data residency compliance.

Does Cerebras have an API?

Yes, Cerebras offers an API for developers.

What platforms does Cerebras support?

Cerebras is available on Web, API.

Information Accuracy

Please note: While we regularly update all tool information including descriptions, features, pricing, and other details, this information may change over time as tools evolve and update their offerings. For the most current and accurate information, we recommend visiting the official website directly. Our goal is to provide you with comprehensive and up-to-date information to help you make informed decisions.