For the last five years, the advice was simple: "Just buy Nvidia." In 2025, that rule is breaking. The rise of Groq and its LPU (Language Processing Unit) has challenged the GPU monopoly, specifically for Inference.

The market is bifurcating:

1. GPUs (Nvidia H100): The King of Training and high-throughput offline batching.

2. LPUs (Groq): The King of Real-Time Latency.

The Physics of Speed: SRAM vs. HBM

Why is Groq so fast? It comes down to memory architecture.

Nvidia (GPU): Uses High Bandwidth Memory (HBM). To execute a model, the chip must fetch weights from HBM to the core. This takes milliseconds. To mask this latency, GPUs "batch" requests—waiting for 64 users to ask a question before processing them all at once. This creates the "Chatbot Paused..." lag.

Groq (LPU): Replaces HBM with massive, on-chip SRAM (230MB per chip). The model weights live physically next to the compute cores. The bandwidth is essentially infinite compared to HBM. There is no need to batch. It processes requests deterministically, one by one, instantly.

500 T/s Tokens per Second (Llama-3-70B on Groq) vs ~60 T/s on standard H100 execution

The Cost of Density

Speed is not free. SRAM is expensive. A single Groq chip has tiny memory capacity (230MB). To fit a 70 Billion parameter model (which is ~140GB in Int8), you need roughly 576 Groq chips networked together.

This means the Capital Expenditure (CapEx) to stand up a Groq rack is higher than a single H100 server. However, Groq has absorbed this complexity and offers an API that undercuts the market.

Economic Verdict

Use Groq (LPU) If:

• Real-Time Voice Agents: If you are building a Siri/Alexa competitor using LLMs, latency > 200ms feels "broken." Groq is the only way to get sub-100ms response times.

• Code Autocomplete: Developers hate waiting. Groq powers completions that feel like you are typing.

• Complex Agentic Loops: If your agent does 50 steps of reasoning (Chain of Thought), a 60 T/s GPU takes minutes. A 500 T/s LPU takes seconds.

Use Nvidia (GPU) If:

• Offline Batching: You have 10,000 documents to summarize overnight. No one is waiting. Throughput/Dollar matters more than Latency.

• Fine-Tuning: You cannot train or fine-tune efficiently on Groq yet.

Conclusion

Latency is the new currency for UX. If your product feels sluggish, switching to Groq is the easiest "Performance Upgrade" you can buy—no code changes required, just a base URL swap.