The fastest LLM inference available - run open models at 800+ tokens per second
Groq provides ultra-fast AI inference using custom LPU (Language Processing Unit) chips that deliver open-weight models like Llama and Mixtral at 800+ tokens per second - 10-50x faster than GPU-based providers.
ShareTool Verdict- 8/10
Essential infrastructure for any latency-sensitive AI application - if your use case can run on an open model, Groq's speed advantage is too significant to ignore
Developers consistently describe Groq as a revelation for inference speed - particularly for voice and real-time applications. The free tier and OpenAI-compatible API drive rapid adoption. Limitations around model selection (open models only) and rate limits are well understood and accepted by the technical audience.
“800 tokens per second is not a marketing number - I clocked it myself. It completely changes what is possible in a voice AI application.”
Hacker News“Switched from OpenAI to Groq for my Llama workloads and cut costs by 75% while making the app feel 10x faster. Should have done this months ago.”
Twitter/XFree
$$0/mo
Pay-per-token
$From $0.05/M tokens/mo
Enterprise
$Custom/mo
Groq uses custom LPU chips designed specifically for the sequential nature of token generation in transformer models. GPU-based inference is optimized for parallel computation (matrix multiplication) but less efficient for the memory-bandwidth-bound work of generating tokens one at a time.
Yes for most use cases - Groq's API is OpenAI-compatible. Change the base URL and API key, keep the same client library and request format. You will need to swap model names to Groq-hosted models (e.g. llama-3.3-70b-versatile instead of gpt-4o).
The free tier is excellent for development and testing but rate limits (typically 30 requests/minute and 14,400 requests/day on popular models) make it impractical for production traffic. Paid capacity is required for production workloads.
No - Groq only hosts open-weight models like Llama, Mixtral, and Gemma. For closed models (GPT-4, Claude, Gemini), you need the respective providers' APIs.
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“Free tier rate limits are fine for dev but you hit the wall fast in production. Make sure you budget for paid capacity before launch.”
Reddit r/LocalLLaMAAnalyzed from community discussions on Hacker News, Reddit, Twitter/X, Product Hunt, G2 · June 2026
Groq's Llama 3.3 70B runs at about $0.59/M input tokens vs GPT-4o at $2.50/M input tokens. For tasks where an open model is sufficient, Groq is 4-5x cheaper with 10-50x the speed.
