Groq

Groq is the AI inference cloud platform built by Groq, Inc.; it trades custom LPU inference chips for ultra-low latency and serves an OpenAI-compatible API through GroqCloud. It only does inference and never touches training — every hosted model comes from third-party open weights, and what Groq builds itself is limited to inference hardware and the inference stack. It exists for developers who treat latency as their core pain point.

Core capabilities

• Custom LPU chips: deterministic dataflow architecture, 256 LPUs per rack and 40 PB/s of SRAM bandwidth, buying stable low latency
• Ultra-fast inference: the company cites 1,000 tokens/sec per user, and Llama 3.3 70B measures about 322 t/s in practice, placing it in the top tier of public APIs
• OpenAI-compatible API: switch to api.groq.com/openai/v1 to migrate existing code, with a complete Vercel and LangChain ecosystem
• Free tier: rate-limited access to every model with no card required — enough for agent prototypes and students practicing
• Multimodal coverage: Chat, Whisper speech-to-text, Orpheus text-to-speech, structured outputs, tool calling and batch processing
• Usage-based pricing: billed per 1M tokens with no monthly fee, and Batch API and Prompt Caching each save roughly another 50%

Use cases Real-time voice agents, low-latency chatbots, interactive agent loops, and prototype validation that needs extremely fast responses. A good fit for developers and teams that rank latency first and can accept open-weight models.

Unique advantages Against Cerebras, Together and Fireworks, Groq's moat is the latency determinism that its own silicon brings; the speed crown is taken by Cerebras on certain models, but the extremely low migration cost and the friendly free tier are rare among peers.

Editorial take The word developers mention most is "lightning fast", and a vendor case study reports 7.41x faster chat and 89% lower cost after migration. Points are deducted for a narrow model catalog (no GPT-4o/Claude), no self-serve fine-tuning, scarce independent review samples, and recent strategic changes. If latency is your core pain point, it deserves a first try.