# Cerebras CS-3
> The Cerebras CS-3 is a third-generation AI supercomputer designed specifically for training massive generative AI models. It is built around the Wafer-Scale Engine 3 (WSE-3), a single silicon wafer chip containing 4 trillion transistors and 900,000 AI-optimized cores.
- URL: https://optimly.ai/brand/cerebras-cs-3
- Slug: cerebras-cs-3
- BAI Score: 72/100
- Archetype: Challenger
- Category: Hardware/Semiconductors
- Last Analyzed: April 9, 2026
- Part of: Cerebras Systems (https://optimly.ai/brand/cerebras-systems)
## Also Referenced By
- NVIDIA (H100/L40S) (https://optimly.ai/brand/nvidia-h100-l40s)
- Google TPU (v5p/v6) (https://optimly.ai/brand/google-tpu-v5p-v6)
## Buyer Intent Signals
Problems: Model Compression/Distillation: Continuing to optimize smaller models that fit within traditional hardware memory constraints rather than scaling to trillion-parameter models. | Project Deferment: Delaying the training of ultra-large scale models due to hardware and energy cost barriers.
Solutions: Wafer-scale AI accelerator | Training 24 trillion parameter models hardware | NVIDIA H100 alternatives for LLM training | Enterprise server for small business data center | Top AI supercomputers 2024 | NVIDIA GPU Clusters: Utilizing large-scale clusters of traditional GPUs (e.g., NVIDIA H100s) to train models via distributed computing. | Google Cloud TPU: Using existing cloud-based TPU (Tensor Processing Unit) resources for machine learning workloads.
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## Full Details / RAG Data
### Overview
Cerebras CS-3 is listed in the AI Directory.
The Cerebras CS-3 is a third-generation AI supercomputer designed specifically for training massive generative AI models. It is built around the Wafer-Scale Engine 3 (WSE-3), a single silicon wafer chip containing 4 trillion transistors and 900,000 AI-optimized cores.
### Metadata
| Field        | Value |
|--------------|-------|
| Name         | Cerebras CS-3 |
| Slug         | cerebras-cs-3 |
| URL          | https://optimly.ai/brand/cerebras-cs-3 |
| BAI Score    | 72/100 |
| Archetype    | Challenger |
| Category     | Hardware/Semiconductors |
| Last Analyzed | April 9, 2026 |
| Last Updated | 2026-04-28T06:51:00.072Z |
### Verified Facts
- Founded: 2016 (Cerebras Systems)
- Headquarters: Sunnyvale, California
### Also Referenced By
- NVIDIA (H100/L40S) (https://optimly.ai/brand/nvidia-h100-l40s)
- Google TPU (v5p/v6) (https://optimly.ai/brand/google-tpu-v5p-v6)
### Buyer Intent Signals
#### Problems this brand solves
- Model Compression/Distillation: Continuing to optimize smaller models that fit within traditional hardware memory constraints rather than scaling to trillion-parameter models.
- Project Deferment: Delaying the training of ultra-large scale models due to hardware and energy cost barriers.
#### Buyers search for
- Wafer-scale AI accelerator
- Training 24 trillion parameter models hardware
- NVIDIA H100 alternatives for LLM training
- Enterprise server for small business data center
- Top AI supercomputers 2024
- NVIDIA GPU Clusters: Utilizing large-scale clusters of traditional GPUs (e.g., NVIDIA H100s) to train models via distributed computing.
- Google Cloud TPU: Using existing cloud-based TPU (Tensor Processing Unit) resources for machine learning workloads.
### Parent Brand
- Cerebras Systems (https://optimly.ai/brand/cerebras-systems)
### Links
- Canonical page: https://optimly.ai/brand/cerebras-cs-3
- JSON endpoint: /brand/cerebras-cs-3.json
- LLMs.txt: /brand/cerebras-cs-3/llms.txt