Groq vs vLLM
Side-by-side comparison of Groq and vLLM: pricing, features, API access, and community ratings.
AI comparison summary
TL;DR: Groq is a hosted inference service built on proprietary LPU hardware optimizing for raw speed and low latency, while vLLM is an open-source serving engine you deploy yourself that maximizes throughput efficiency through advanced memory management (PagedAttention) and supports virtually any hardware platform. Choose Groq for instant access to extremely fast inference without infrastructure management, or vLLM if you need self-hosted deployment, want fine-grained control over optimization techniques like quantization and distributed inference, or require flexibility across different hardware vendors beyond NVIDIA/LPU.
| Category | AI infrastructure | AI infrastructure |
| Pricing | Freemium | Freemium |
| Starting price | ||
| Free tier | ||
| Audience | All audiences | All audiences |
| API available | ||
| Open source | ||
| Self-hostable | ||
| Model provider | Groq (third-party models hosted on LPU infrastructure) | |
| Founded | 2016 | 2023 |
| Headquarters | San Jose, USA | Berkeley, United States |
| Key strengths |
|
|
