Groq

What if your AI inference was born for speed, not adapted for it?

Automated product research from public website content. No hands-on app test is recorded for this profile. Pricing source and check date are shown below where available.

Research fitSource-based assessment: Groq offers a compelling solution for high-performance AI inference, leveraging its unique LPU architecture to deliver speed and affordability that can significantly impact operational costs and application responsiveness.

Groq delivers a purpose-built LPU (Language Processing Unit) architecture designed for AI inference, offering significantly faster and more affordable processing compared to traditional GPUs. It provides a cloud platform, GroqCloud, for developers to access leading GenAI models with predictable costs and scalable performance.

Visit Groq

Visit Groq

Key Features:

LPU Architecture for fast inference
GroqCloud platform for model access
OpenAI compatible API
Support for LLMs, STT, TTS, and image-to-text models
Prompt caching for cost savings and faster responses

Pros

Developers needing high-speed, low-latency AI inference for large language models
Enterprises requiring predictable and affordable AI inference costs at scale
Teams building agentic AI applications that integrate web search and code execution

Cons

Focus is primarily on inference, not model training.
Some advanced models and features are enterprise-only.
While compatible with OpenAI API, it's a different underlying architecture.

Pricing

freemiumFree tier

Starting at:Pay Per Token

Free tier:Build and Test on Groq, Community Support, Zero-data Retention Available

Plans

Free: Build and Test on Groq, Community Support, Zero-data Retention Available
Developer: Pay Per Token, Higher Token Limits, Chat Support, Flex Service Tier, Batch Processing, Spend Limits, Prompt Caching
Enterprise: Contact Us, Custom Models, Regional Endpoint Selection, Performance Tier, Scalable Capacity, Dedicated Support, LoRA Fine-Tunes

Categories:

AI Infrastructure Code & Development Chatbots & Assistants

Tags:

inference LPU LLM API cloud speed cost-effective developer tools text-to-speech speech-to-text

Share:

Quick Decision

Try if: You need lightning-fast, cost-effective AI inference for large language models and are looking for an OpenAI-compatible API with predictable pricing.

Skip if: You are primarily focused on AI model training or require a wide array of niche AI models not currently supported.

Not for: Users primarily focused on AI model training rather than inference; Individuals with minimal AI inference needs where extreme speed is not critical

Trust Signals

Founded
2016
Users
3m+ developers and teams
Team Size
large
Funding
$750 Million (September 2025)

Compliance

SOC 2GDPRHIPAA

Notable Customers

McLaren F1 TeamPGA of AmericaFintoolOpennote

Tech Details

Platforms

webapi

Integrations

OpenAI API compatibleBrowserBase MCPBrowser Use MCPExa MCPFirecrawl MCPHuggingFace MCPParallel MCPStripe MCPTavily MCP

AI Model
GPT OSS 20B, GPT OSS 120B, Llama 3.3 70B, Llama 3.1 8B, Qwen 3.6 27B, Minimax M2.7, Canopy Labs Orpheus, Whisper V3 Large

Open Source

Support

Channels

community forumchatdedicated support (enterprise)

Company

Name
Groq
Location
United States

Groq was established in 2016 with the singular focus of delivering high-performance AI inference. They developed the LPU, a custom-built chip architecture, to provide fast, low-cost, and scalable AI processing solutions.

FAQ

What is Groq and how is it different from other AI inference providers?

Groq is an AI inference platform that utilizes its custom-built LPU (Language Processing Unit) architecture, designed specifically for inference. This differentiates it from providers relying on GPUs, offering significantly faster, lower-latency, and more cost-effective AI processing for large language models.

What models are available on GroqCloud and what are their pricing structures?

GroqCloud supports a range of Large Language Models (LLMs) like GPT OSS, Llama, and Qwen, as well as Text-to-Speech (TTS) and Automatic Speech Recognition (ASR) models. Pricing is usage-based, calculated per million input and output tokens, with specific rates varying by model. A free tier is available for building and testing.

Does Groq offer enterprise solutions or on-premise deployment options?

Yes, Groq offers enterprise-level access with custom models, regional endpoint selection, scalable capacity, and dedicated support. For on-premise deployment, GroqRack allows the LPU powering GroqCloud to be deployed locally, ideal for regulated industries or air-gapped environments.

Use Cases

Developers needing high-speed, low-latency AI inference for large language models
Enterprises requiring predictable and affordable AI inference costs at scale
Teams building agentic AI applications that integrate web search and code execution