Last updated: 2026-07-01
Groq is an AI inference platform built by Groq Inc. that runs open-source language models such as Llama, Qwen, and GPT-OSS on custom Language Processing Unit (LPU) chips instead of GPUs, serving more than 2 million developers worldwide with deterministic, low-latency responses for production applications.
About Groq
Groq is an AI inference platform delivering ultra-fast, cost-effective language model inference through its proprietary Language Processing Unit (LPU) technology. Founded in 2016 by former Google TPU engineers, Groq offers GroqCloud, a cloud-based API providing access to open-source models including Llama, Qwen, Mixtral, and OpenAI's GPT-OSS series. The LPU architecture is purpose-built for inference, achieving record-breaking throughput of 1,000+ tokens/second on certain models and minimal latency, with sub-300ms first-token response times compared to GPU-based competitors. Groq serves over 2 million developers globally and enterprise clients including the McLaren F1 Team, enabling real-time AI applications with deterministic, predictable performance. The platform supports full OpenAI API compatibility, making integration straightforward for existing projects.
Pricing
Free tier with daily request limits (14,400 req/day on Llama 3.1 8B, 6,000 on Llama 3.3 70B). Pay-as-you-go pricing: Llama 3.1 8B at $0.05 input/$0.08 output per 1M tokens; Llama 3.3 70B at $0.59 input/$0.79 output; GPT-OSS 120B premium tier available. Batch API offers 50% discount for non-urgent workloads. Enterprise custom pricing available.
Key Features
- Language Processing Unit (LPU) Hardware: Custom-built inference chips with SRAM-centric design and deterministic architecture, delivering 10x faster inference than traditional GPUs without memory bandwidth bottlenecks
- OpenAI Compatible API: Drop-in replacement for OpenAI API - integrate with just two lines of code by changing base_url and API key
- Multi-Model Ecosystem: Access to 30+ open-source models across the Llama, GPT-OSS, Qwen, Kimi K2, and Mistral families, including the 120B-parameter GPT-OSS flagship, plus specialized models for vision, code, and reasoning
- Sub-Second Latency: The platform's fastest hosted models return 275+ tokens per second with consistent throughput across varying input lengths, keeping response times predictable under real-world load
- Built-In Tools & Compound AI: Native web search, code execution, browser automation, and MCP integrations for intelligent agent-based applications
- Enterprise-Grade Compliance: SOC 2, GDPR, HIPAA compliant; global data center deployment with regional availability for minimal latency and on-premises GroqRack deployment option
Pros
- Consistently among the fastest inference options available, roughly 6 to 20 times quicker than typical GPU-hosted APIs for the same open-source models
- Pay-as-you-go pricing that undercuts typical GPU-based inference costs, with no minimum spend and no long-term contract required
- Free tier with generous daily limits and no credit card required for experimentation
- OpenAI API compatibility enables quick migration from existing projects with minimal code changes
- Deterministic performance with low variance, critical for production applications
Cons
- Limited to open-source models; no proprietary frontier models like GPT-4 or Claude
- Context window limitations on some models (8-128K tokens) compared to long-context specialists
- Newer platform with smaller ecosystem compared to OpenAI/Anthropic established integrations
- Output tokens are billed at a higher rate than input tokens across every paid tier
Frequently Asked Questions
How much does Groq cost in 2026?
Groq bills paid usage per token, with price scaling by model size: Llama 3.1 8B runs $0.05 per 1M input tokens and $0.08 output, while the larger Llama 3.3 70B costs $0.59 input and $0.79 output per 1M tokens. The Batch API cuts those rates by 50 percent for workloads that can wait. Enterprise customers get custom volume pricing instead of the public per-token rates.
Is Groq free to use?
Yes. The free tier lets you call Llama 3.1 8B up to 14,400 times a day and Llama 3.3 70B up to 6,000 times a day, with no credit card needed to start. Once you exceed those daily caps, requests switch to the pay-per-token pricing above.
What are the best alternatives to Groq?
The closest alternatives are Together AI, Fireworks AI, and Baseten. Together AI offers a wider range of models and supports fine-tuning, which Groq does not. Fireworks AI focuses on compound AI systems with built-in function calling, while Baseten specializes in custom model deployment on GPU infrastructure rather than proprietary LPU hardware.
How does Groq compare to Together AI in 2026?
Compared to Together AI, Groq's LPU hardware delivers noticeably higher tokens-per-second throughput and more predictable latency on shared models like Llama. Together AI counters with a broader model catalog, native fine-tuning, and support for custom model deployment, features Groq does not offer. Teams that need raw inference speed pick Groq; teams that need model flexibility pick Together AI.
How do you get started with Groq?
Create a free account at console.groq.com to get an API key. Because Groq is fully OpenAI API compatible, existing OpenAI SDK projects can switch over by changing the base URL and key, usually in under ten minutes. New users can test models directly in the GroqCloud playground before writing any code.
Top Alternatives
- Together AI: Pick Groq for fastest LPU inference; pick Together for model variety and training.
- Fireworks AI: Pick Groq for raw LPU speed; pick Fireworks for compound AI systems and function calling.
- Baseten: Pick Groq for managed LPU cloud; pick Baseten for custom model deployment on GPU.
HokAI guides covering Groq
- How to Choose the Right LLM: A Practical Guide to GPT, Claude, Gemini, Llama, DeepSeek, and Perplexity: Choosing an LLM in August 2026 means new GPT-5.6 pricing, an expiring Claude Sonnet 5 discount, and Meta exiting open-weight models. This guide has the numbers.