Question 1

What Is Groq?

Accepted Answer

Groq is a cloud inference provider running open-weight models (Llama 3, Mixtral, Gemma) on custom LPU (Language Processing Unit) hardware. Its core selling point is speed — sub-second first-token latency and very high throughput — at competitive prices. It's an API service, not a model provider; the models are Meta's and Mistral's, run on Groq's silicon.

Question 2

Is Groq Worth Using in 2026?

Accepted Answer

Groq's heat score is 8/100 with a -38 7-day delta, continuing a multi-cycle decline. Inference speed is no longer the bottleneck it was in 2024 — OpenAI, Anthropic, and Google have all improved latency, and most production apps are quality-constrained, not speed-constrained. Practitioners building provider-agnostic stacks via LiteLLM can include Groq as a routing option for latency-critical paths without committing their architecture to it.

Question 3

Groq vs Ollama: Cloud Inference vs Local Inference

Accepted Answer

Groq gives you fast cloud inference on open-weight models with no hardware requirement — pay per token, no ops overhead. Ollama runs the same models locally on your own hardware — zero token cost, full data privacy, but limited by your GPU. For privacy-sensitive workloads or high sustained volume: Ollama. For fast cloud prototyping without local GPU: Groq. Both are less relevant for production if you need GPT-4o or Claude quality, which Groq doesn't offer.