Keywords AI
Groq vs Modal
Compare Groq and Modal side by side. Both are tools in the Inference & Compute category.
Quick Comparison
| Category | Inference & Compute | Inference & Compute |
| Pricing | Freemium | Usage-based |
| Best For | Developers building real-time AI applications where inference speed is the top priority | Python developers who want serverless GPU infrastructure without managing containers or Kubernetes |
| Website | groq.com | modal.com |
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When to Choose Groq vs Modal
- Real-time AI applications needing lowest latency
- Interactive conversational AI
- High-throughput batch inference
- Serverless model inference
- Data processing pipelines
- Batch jobs with GPU acceleration
About Groq
Groq builds custom AI inference chips (Language Processing Units / LPUs) designed for extremely fast token generation. Groq's cloud platform offers the fastest inference speeds in the market, generating hundreds of tokens per second for models like Llama and Mixtral. The company's hardware architecture eliminates the memory bandwidth bottleneck that limits GPU-based inference, making it ideal for real-time and latency-sensitive AI applications.
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.
Browse all Inference & Compute tools →