====== Cerebras Inference ======

**Cerebras** is an AI hardware and inference company built around the **Wafer-Scale Engine (WSE)**, the largest processor ever built. Rather than cutting a silicon wafer into individual chips, Cerebras integrates an entire wafer into a single processor, fundamentally eliminating the memory bandwidth bottleneck that constrains GPU-based inference. The Cerebras Inference Platform launched in August 2024 and delivers speeds 10-70x faster than GPU solutions.((source [[https://www.cerebras.ai/inference|Cerebras Inference]]))

===== Wafer-Scale Engine (WSE-3) =====

The latest WSE-3 processor represents a radical departure from conventional chip design:

  * **4 trillion transistors** on a single wafer
  * **900,000 AI cores**
  * **125 petaflops** of AI compute
  * **44 gigabytes of on-chip SRAM**

The 44 GB of SRAM co-located directly on the silicon near compute cores is the critical advantage. For comparison, an NVIDIA H100 GPU has approximately 40 megabytes of on-chip memory. This eliminates the external memory access bottleneck that limits GPU inference throughput.((source [[https://thedataexchange.media/cerebras-inference/|Cerebras Inference Deep Dive]]))

===== Speed Records =====

Cerebras has achieved remarkable inference benchmarks:

  * **Qwen3-32B reasoning model**: Answers in as little as 1.2 seconds (60x faster than competing implementations including OpenAI o3)
  * **General throughput**: Over 3,000 tokens per second
  * **Meta Llama 4**: Up to 20x faster than typical GPU speeds
  * **Reasoning models**: Tasks that traditionally required 30-90 seconds complete in seconds on Cerebras infrastructure((source [[https://siliconangle.com/2025/05/15/cerebras-systems-blazes-trail-ai-inference-powering-advanced-reasoning-real-time/|Cerebras Blazes Trail in AI Inference]]))

^ Aspect ^ Cerebras WSE-3 ^ GPU (e.g., H100) ^
| Architecture | Entire silicon wafer as single processor | Individual cut chips |
| On-chip Memory | 44 GB SRAM co-located with cores | ~40 MB on-chip memory |
| Inference Speed | 10-70x faster throughput | Baseline |
| Reasoning Latency | Seconds (e.g., 1.2 sec for Qwen3-32B) | 30-90 seconds |

===== Infrastructure =====

Cerebras operates at significant scale with plans for continued expansion:

  * 8 data center facilities across the United States and Europe
  * Thousands of CS-3 systems deployed
  * Target capacity of over 40 million tokens per second by end of 2025((source [[https://www.cerebras.ai/inference|Cerebras Infrastructure]]))

===== Supported Models =====

The platform supports a growing range of open-weight models:

  * **Qwen3-32B** (Alibaba's reasoning model)
  * **Meta Llama 4**
  * **DeepSeek R1**
  * **OpenAI gpt-oss-safeguard-120b** (Cerebras is the fastest inference provider)
  * **Mistral AI** models

Custom fine-tuned versions of standard open-weight models can typically be onboarded within 30 minutes.((source [[https://www.cerebras.ai/blog/cerebras-october-2025-highlights|Cerebras October 2025 Highlights]]))

===== API =====

The Cerebras Inference Platform operates as a cloud-based service accessible via API. Enterprise customers include AI model makers such as Mistral AI and AI-powered search engines such as Perplexity AI.

===== Recent Developments =====

  * Became the fastest inference provider for OpenAI's newest open-source models (October 2025)
  * Opened new data center in Oklahoma City
  * Presented nine research papers at NeurIPS 2025 spanning pretraining to inference
  * CEO Andrew Feldman stated the platform is "fast enough to reshape how real-time AI gets built"((source [[https://www.cerebras.ai/blog/cerebras-at-neurips-2025-nine-papers-from-pretraining-to-inference|Cerebras at NeurIPS 2025]]))

===== See Also =====

  * [[groq_inference|Groq Inference]]
  * [[together_ai|Together AI]]
  * [[fireworks_ai|Fireworks AI]]

===== References =====