Keywords AI

Cerebras vs Modal

Compare Cerebras and Modal side by side. Both are tools in the Inference & Compute category.

Quick Comparison

Cerebras
Cerebras
Modal
Modal
CategoryInference & ComputeInference & Compute
PricingUsage-basedUsage-based
Best ForEnterprises and developers who need the fastest possible LLM inferencePython developers who want serverless GPU infrastructure without managing containers or Kubernetes
Websitecerebras.netmodal.com
Key Features
  • Wafer-scale inference chips
  • Record-breaking inference speed
  • Simple API deployment
  • Optimized for large language models
  • Custom silicon architecture
  • Serverless cloud for AI
  • Python-native container orchestration
  • Auto-scaling GPU infrastructure
  • Pay-per-second billing
  • Built-in web endpoints
Use Cases
  • Ultra-fast LLM inference
  • Real-time AI applications
  • High-throughput text generation
  • Enterprise inference infrastructure
  • Latency-critical AI deployments
  • Serverless model inference
  • Data processing pipelines
  • Batch jobs with GPU acceleration
  • Development environments with GPUs
  • Auto-scaling AI APIs

When to Choose Cerebras vs Modal

Cerebras
Choose Cerebras if you need
  • Ultra-fast LLM inference
  • Real-time AI applications
  • High-throughput text generation
Pricing: Usage-based
Modal
Choose Modal if you need
  • Serverless model inference
  • Data processing pipelines
  • Batch jobs with GPU acceleration
Pricing: Usage-based

About Cerebras

Cerebras builds the world's largest AI chips—wafer-scale processors that contain millions of cores on a single silicon wafer. The Cerebras CS-2 system delivers massive parallelism for AI training and ultra-fast inference for open-source models. Through Cerebras Inference, developers can access some of the fastest LLM inference speeds available, particularly for Llama models.

About Modal

Modal is a serverless cloud platform for running AI workloads with zero infrastructure management. Developers write Python code and Modal handles containerization, GPU provisioning, scaling, and scheduling automatically. The platform supports GPU-accelerated functions, scheduled jobs, web endpoints, and batch processing, making it particularly popular for ML pipelines, model serving, and data processing tasks.

What is Inference & Compute?

Platforms that provide GPU compute, model hosting, and inference APIs. These companies serve open-source and third-party models, offer optimized inference engines, and provide cloud GPU infrastructure for AI workloads.

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