Groq

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Ultra-fast LLM inference API using custom LPU hardware - 400–800 tokens/second on Llama 3.3, Gemma, and Mixtral models.

Groq is an AI inference company that builds its own Language Processing Unit (LPU) chip - purpose-built silicon for LLM inference rather than training. The result is inference speeds of 400–800 tokens per second on Llama 3.3 70B, Gemma 2, Mixtral, and other open-source models, making Groq the fastest publicly available LLM API by a significant margin. Groq does not develop its own LLMs - it runs open-weight models from Meta, Google, and Mistral on its proprietary hardware. Groq Cloud is available as an API compatible with the OpenAI SDK for easy integration. GroqCloud is free for development with usage limits, and paid plans offer higher throughput. Backed by $640M at a $2.8B valuation.

#llm

#inference

#api

#developer-tools

#open-source

#fast-inference

#llama

#hardware-ai

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Key Features

LPU (Language Processing Unit) - custom silicon delivering 400–800 tokens/second inference
Runs Llama 3.3 70B, Llama 3.1 405B, Gemma 2, Mixtral, Whisper, and other open-weight models
OpenAI SDK compatible API - drop-in replacement for OpenAI calls in existing codebases
Free tier with rate-limited access for development and prototyping
Sub-100ms time-to-first-token for real-time streaming applications
Whisper-large-v3 speech-to-text at the fastest transcription speed available
Batch inference API for high-volume async workloads at lower cost

Use Cases

Developers building real-time AI chat and voice applications requiring ultra-low latency
Startups using open-weight models (Llama, Gemma) at GPT-4-competitive cost
Production applications where inference speed directly impacts user experience quality
Researchers running rapid iteration experiments needing fast model responses
Voice AI applications using Whisper transcription at sub-1-second latency
High-volume inference workloads switching from OpenAI to reduce cost via open models

Pros

400–800 tokens/second is 10× faster than typical cloud GPU inference - real-time streaming is genuinely different UX
OpenAI SDK compatibility means switching from GPT-4 to Llama 3.3 on Groq requires changing 2 lines of code
Free development tier with no credit card required - instant access to the fastest inference available

Cons

Limited model selection - only runs open-weight models; no GPT-4o, Claude, or Gemini Ultra access
Context window size limited vs. frontier model providers - Llama 3.3 70B at 128K vs Claude 4 at 200K+
Not an LLM lab - model quality ceiling is determined by Meta/Google/Mistral, not Groq itself