Groq vs Vast.ai

Custom Language Processing Units run inference, with 256 LPUs and 128 GB of on-chip SRAM per rack

Drop-in replacement for the OpenAI API at api.groq.com/openai/v1, including a Responses API

GroqMetal bare-metal infrastructure, GroqCore inference stack, and GroqAssured enterprise governance, each including the layers below

Text generation plus speech-to-text, text-to-speech, OCR and image recognition, and content moderation models

Compound systems that combine models with web search, code execution, remote MCP tools, and Google Workspace connectors

Performance, flex, and batch processing tiers, plus prompt caching, structured outputs, and LoRA inference

Prices set by supply and demand across the platform with no list prices or hidden fees

GPU Cloud for full control, Serverless for zero-ops inference, Clusters for large-scale training

CLI, Python SDK, and REST API for programmatic GPU provisioning, installed together via a single package

API-native workflow intended for AI agents to search, procure, and release compute autonomously

Prebuilt templates for popular open-source models, plus custom templates any GPU can run with one click

Scale from $5 to 20,000 GPUs across 40+ data centers without contracts or minimums