Groq

What is Groq?

Groq provides the fastest AI inference available, running open-source language models at speeds 10-20x faster than conventional GPU-based providers. The company designed custom silicon called Language Processing Units (LPUs) specifically for the sequential nature of large language model inference, achieving deterministic performance that eliminates the variable latency plaguing GPU-based systems. Where a typical cloud provider might deliver 30-50 tokens per second for Llama 3.3 70B, Groq routinely exceeds 300 tokens per second — a difference you feel immediately in interactive applications.

The platform focuses exclusively on open-source and open-weight models: Llama 3.1, Llama 3.3, Llama 4 Scout, Qwen 3, Mistral, and others. Groq does not host proprietary models like GPT-4o or Claude — the value proposition is making open-source models fast enough that they become viable alternatives to proprietary options for latency-sensitive applications. The API is OpenAI-compatible, so switching from OpenAI to Groq typically requires changing only the base URL and API key. This makes Groq compelling for developers who want to reduce costs while maintaining response speed.

Groq offers three billing tiers: a generous free tier with no credit card required, a Developer tier with 25% token discount and 10x rate limits, and custom Enterprise plans for high-volume deployments. Pricing starts at $0.05 per million tokens for smaller models like Llama 3.1 8B and scales to approximately $1.50 per million tokens for the largest models. Batch API processing provides a 50% discount for non-urgent workloads, and prompt caching delivers 50% savings on repeated inputs — both significant for production applications.

Beyond the API, Groq offers GroqChat — a free web interface for interacting with models directly, similar to ChatGPT but powered by open-source models on LPU hardware. The combination of speed, affordability, and open-model support makes Groq the go-to platform for developers building real-time AI applications where latency matters more than model breadth.

Groq Pricing

Groq uses pay-per-token pricing that varies by model. The free tier requires no credit card and provides access to every model with rate limits.

• Free Tier — $0 · Access to all models · Rate-limited · No credit card required
• Developer Tier — Pay-as-you-go · 25% discount on all tokens · 10x base rate limits · Credit card required
• Enterprise — Custom pricing · On-prem deployment options · Dedicated capacity · SLA guarantees

Sample model pricing (per 1M tokens, input/output):

• Llama 3.1 8B Instant — $0.05 / $0.08
• Llama 4 Scout (17Bx16E) — $0.11 / $0.34
• Qwen 3 32B — $0.29 / $0.59
• Llama 3.3 70B Versatile — $0.59 / $0.79

Batch API saves 50% on non-urgent workloads. Prompt caching saves 50% on repeated inputs.

Key Features

• LPU-Based Ultra-Fast Inference — Custom Language Processing Unit hardware delivers 300+ tokens/second for Llama 3.3 70B — 10-20x faster than GPU-based providers with deterministic latency
• Open-Source Model Library — Hosts Llama 3.1, Llama 3.3, Llama 4 Scout, Qwen 3, Mistral, and other open-weight models optimized for LPU execution
• OpenAI-Compatible API — Drop-in API replacement for OpenAI — change the base URL and API key to switch existing applications to Groq with no code rewrite
• Generous Free Tier — Access every model without a credit card, with rate limits sufficient for prototyping, testing, and personal projects
• Batch API Processing — Submit thousands of requests at once for non-urgent workloads and receive a 50% discount on token costs — ideal for data processing and evaluation
• Prompt Caching — Automatically caches repeated prompt prefixes and charges 50% less for cache hits, reducing costs for applications with common system prompts
• JSON Mode & Function Calling — Structured output support including guaranteed JSON formatting and function/tool calling for building reliable agent workflows
• GroqChat Web Interface — Free browser-based chat interface for interacting with all hosted models directly, similar to ChatGPT but running on LPU hardware
• Vision Model Support — Multimodal models that accept image inputs alongside text for visual understanding, image analysis, and OCR tasks
• Developer Dashboard — Real-time usage monitoring, cost tracking, rate limit visibility, and API key management for production deployments

Pros & Cons

Best For

Developers building real-time AI applications where response latency directly impacts user experience — chatbots, coding assistants, and interactive agents. Startups and indie developers who want powerful open-source model inference at a fraction of OpenAI or Anthropic pricing. Teams migrating from proprietary APIs who need an OpenAI-compatible endpoint running open-source models without rewriting application code. Data engineers and ML teams running batch inference on large datasets where Groq's Batch API provides 50% cost savings over real-time rates.