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commercial Pay-per-use

Ultra-fast LLM inference powered by custom LPU silicon, delivering 500+ tokens/sec for open-source models

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500+ Tokens/sec
<50ms Time to First Token
10+ Models Available

Overview

Groq provides the fastest LLM inference API in the market, powered by their custom-designed Language Processing Unit (LPU) silicon. Unlike GPUs that were designed for graphics and adapted for AI, the LPU was purpose-built from the ground up for sequential inference workloads like language models. This results in dramatically lower latency and higher throughput - often 10x faster than GPU-based alternatives. Groq hosts popular open-source models including Llama 3, Mixtral, and Gemma, making it ideal for applications where response speed is critical.

The Verdict

Who Should Use Groq?

Best For

  • Real-time chat applications needing instant responses
  • Voice AI and conversational agents
  • High-throughput batch processing
  • Cost-sensitive open-source model deployment
  • Latency-critical production workloads

Not Ideal For

  • Proprietary frontier models (GPT-4, Claude)
  • Fine-tuned custom models
  • Very long context requirements (>128K)
  • Image/multimodal generation

What's Great

  • Fastest inference speeds in the industry (500+ tok/s)
  • Sub-50ms time-to-first-token latency
  • Competitive pricing on open-source models
  • OpenAI-compatible API for easy migration
  • Generous free tier for experimentation
  • Simple, transparent pay-per-token pricing
Groq Official · Artificial Analysis

Watch Out For

  • Limited to open-source models only
  • No fine-tuning or custom model hosting
  • Smaller context windows than some competitors
  • Rate limits can be restrictive on free tier
  • Fewer model options than Together AI or Fireworks
Groq Docs

Pricing

Free Tier
$0
Rate-limited, great for testing
Llama 3.1 70B
$0.59/M tokens
Input tokens, output $0.79/M
Llama 3.1 8B
$0.05/M tokens
Input tokens, output $0.08/M
Mixtral 8x7B
$0.24/M tokens
Input tokens, output $0.24/M
View all features & details

LPU Technology

  • Purpose-built for sequential inference
  • Deterministic performance (no batching variance)
  • Single-chip architecture (no network overhead)
  • Optimized for autoregressive decoding
  • Lower power consumption than GPUs

Supported Models

  • Llama 3.1 (8B, 70B, 405B)
  • Llama 3.2 (1B, 3B, 11B Vision)
  • Mixtral 8x7B
  • Gemma 2 (9B, 27B)
  • Whisper Large v3 (speech-to-text)

API Features

  • OpenAI-compatible endpoints
  • Streaming responses
  • JSON mode
  • Tool/function calling
  • Vision models support

Enterprise

  • Dedicated capacity available
  • Higher rate limits
  • SLA guarantees
  • Priority support

Benchmarks

500+
Tokens/Second (Llama 3 70B)
Output generation speed for large models
Artificial Analysis
<50ms
Time to First Token
Industry-leading latency for real-time apps
Groq Official
10x
Faster Than GPUs
Typical speedup vs GPU-based inference
Groq LPU
800+
Tokens/Sec (Llama 3.1 8B)
Smaller models achieve even higher throughput
Artificial Analysis

How It Compares

Feature Groq Together AI Fireworks AI Cerebras
Speed (tok/s) 500+ (LPU) 100-200 150-250 400+
Time to First Token <50ms 100-300ms 80-150ms <100ms
Model Selection 10+ models 100+ models 50+ models 10+ models
Fine-tuning No Yes Yes No
Custom Silicon LPU GPU GPU Wafer-Scale
Free Tier Yes Yes Yes Yes
Best For Speed-critical apps Model variety Balanced Speed + scale

User Reviews

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