Cerebras - Run AI at Ultra Fast Speed

AI inference 15x faster than GPUs - code at the speed of thought

Unclaimed

Updated Jul 2026 · Added Jun 2026

cerebras.ai

Ai Code GeneratorsFreeai-code-assistants

Visit Cerebras

Share: X in LinkedIn

Add your screenshot here

Image or video shown in this spot

Follow Cerebras

What is Cerebras?

Cerebras provides ultra-fast AI inference through its Wafer-Scale Engine, a specialized AI chip that delivers up to 15x faster performance than GPUs. The platform supports multiple deployment options - cloud, dedicated, and on-prem - enabling developers to run open models like Llama, Qwen, and GLM with production-grade speed and reliability. It's designed for enterprises, startups, and developers building real-time AI applications requiring low-latency reasoning and instant responses.

Explore Cerebras

Need help implementing Cerebras - Run AI at Ultra Fast Speed?

Find verified specialists who work with Cerebras - Run AI at Ultra Fast Speed

Browse specialists

Key Features of Cerebras

Wafer-Scale Engine hardware 58x larger than GPUs
Up to 1,500+ tokens per second inference speed
Multimodal model support (Gemma, GLM, Qwen, Llama, GPT-OSS)
OpenAI API compatibility for drop-in integration
Cloud, dedicated, and on-premises deployment options
Train, fine-tune, and serve on single platform
Sub-second complex reasoning and instant voice responses
Enterprise-grade reliability at scale

Who Should Use Cerebras?

Powering real-time AI copilots and search applications

Multi-step workflow execution without delays

Deep search and complex reasoning applications

Voice AI with instant, accurate responses

Intelligent research agents for drug discovery

Genomics data analysis for clinical decision-making

Enterprise search and productivity features

Cerebras: Pros & Cons

✓Pros

15x faster inference than GPUs with 58x larger compute engine
Leading price-performance ratio reducing AI infrastructure costs
Sub-30 second setup with OpenAI API compatibility
Multiple deployment options for flexibility and control
Battle-tested at scale by OpenAI, Meta, and Global 1000 enterprises
Unified platform for training, fine-tuning, and serving
Supports latest frontier models and multimodal capabilities
Instant response times enable better reasoning and output quality

Frequently Asked Questions about Cerebras

Can I use Cerebras with OpenAI API code without rewriting it?

Yes. Cerebras supports OpenAI API compatibility, so you can swap in its endpoints as a drop-in replacement for existing integrations. This means codebases written for OpenAI can point to Cerebras infrastructure with minimal changes to connection details.

What's the actual token-per-second throughput I should expect for inference?

Cerebras advertises 1,500+ tokens per second on its Wafer-Scale Engine hardware. The exact throughput will depend on which model you run and your specific prompt structure, but this figure represents the platform's peak capacity for single-request processing.

Does Cerebras support Llama and other open-source models, or only proprietary ones?

Cerebras runs open models including Llama, Qwen, GLM, and Gemma alongside proprietary options. The platform is designed to serve multiple frontier models, giving you flexibility in which weights you deploy rather than locking you into a single vendor's architecture.

Can I train and fine-tune models on Cerebras, or just run inference?

Cerebras offers a unified platform for training, fine-tuning, and serving. You're not limited to inference alone; you can refine models on the same hardware before pushing them to production, which simplifies the workflow for teams building custom AI applications.