Groq

Groq is an AI inference platform that runs open models at exceptionally high speed on its own LPU hardware. It is built for developers and product teams whose applications need instant, low-latency AI responses rather than the slower generation typical of general cloud APIs.

Key features

• Very high tokens-per-second inference on popular open-weight models.
• OpenAI-compatible API so existing code can switch with minimal changes.
• GroqCloud console with playground, usage metrics and API key management.
• Support for chat, tool calling, speech-to-text and vision-capable models.
• Batch and streaming responses for real-time interfaces.

Who it is for

• Developers building voice assistants and live chat where delay breaks the experience.
• Teams running high-volume classification, extraction or summarisation jobs.
• Startups that want frontier-style capability at open-model cost.
• Engineers benchmarking latency before committing to a model provider.

Pricing

Groq has a free developer tier with rate-limited access to test real workloads, then pay-as-you-go pricing per million input and output tokens that varies by model. Enterprise arrangements cover dedicated capacity and higher throughput commitments.

Why people choose it

Speed changes what you can build. When a model replies in a fraction of a second, an AI feature stops feeling like a loading screen and starts feeling like part of the interface, which is why Groq shows up in live voice agents, autocomplete and agent loops that make many sequential calls. The OpenAI-compatible endpoint keeps migration cheap: teams point their SDK at a new base URL and keep the rest of their code. Combined with open-model pricing, that makes it straightforward to run the same task hundreds of thousands of times a day without the bill scaling the way it would on premium proprietary models.