Key features
- LPU custom inference hardware
- 500+ tokens/second on Llama 70B
- OpenAI-compatible API
- Open-weight model focus
Best for
- Voice agents and real-time applications
- High-throughput batch generation
- User-facing chat interfaces
Limitations to know
- ! Smaller model selection than Together
- ! Capacity sometimes constrained on launch days
About Groq
Groq is a LLM hosting & inference tool from Groq, launched in 2016. Custom LPU inference hardware delivering 10-20x faster token throughput than GPU-based alternatives. The right choice when latency dominates.
Notable capabilities include LPU custom inference hardware, 500+ tokens/second on Llama 70B, and OpenAI-compatible API. Teams typically deploy Groq for voice agents and real-time applications and high-throughput batch generation.
Common trade-offs to weigh: smaller model selection than Together and capacity sometimes constrained on launch days. AIMenta editorial take for APAC mid-market: For any latency-critical use case (voice, chat), Groq is the right answer. The throughput advantage is real and reproducible.
Where AIMenta deploys this kind of tool
Service lines that build, integrate, or train teams on tools in this space.
Beyond this tool
Where this category meets practice depth.
A tool only matters in context. Browse the service pillars that operationalise it, the industries where it ships, and the Asian markets where AIMenta runs adoption programs.
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