Groq vs Novita 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

One endpoint for 200+ text, image, audio and video models, callable with existing OpenAI client libraries

Qwen, DeepSeek, GLM, Kimi, MiniMax, Llama, Gemma and Nemotron families served serverlessly with per-token billing

Cache-read pricing published separately from standard input pricing on most chat models

Per-second serverless GPU jobs, on-demand instances, and bare-metal clusters with H100 and H200 hardware

Dedicated deployments for workloads that need reserved capacity rather than shared serverless throughput

Isolated runtimes for agent workloads that call models and execute tools, billed per second