December 27, 2025
Panic buy or power play?
Nvidia Just Paid $20B for a Company That Missed Its Revenue Target by 75%
Groq isn’t Elon’s bot — it’s “speed chips,” and the crowd says Nvidia panic-bought
TLDR: Nvidia bought Groq for $20B, snapping up a speed-focused AI chip maker that missed revenue targets. Commenters argue it’s either a savvy move to kill future rivals or proof the AI bubble’s overheating, with snark about regulators snoozing and startups becoming Big Tech’s R&D farms.
Nvidia just threw a wild $20 billion at Groq — not Elon’s Grok chatbot, but the chip upstart that makes ultra-fast “Language Processing Units” so AI replies feel instant. Cue chaos in the comments. The loudest chorus calls it a monopoly move: “Nvidia is stifling innovation,” fumes one user, with others raging that regulators are napping while Big Tech speed-runs the AI land grab. Another camp shrugs: this is chess, not checkers — buy the threat before it grows teeth.
The tech explainers tried to keep it simple: Groq’s chips are built for speed, like bringing the grocery list to the store instead of calling home every aisle. But the community drama wasn’t about circuits — it was about power. One cynic dropped the mic: startups are just “low-risk R&D for Big Tech now,” linking a think piece to prove it. There was snark too: “That probably explains why the Groq board took the deal,” implying a fat exit over future dreams. And meta-drama erupted when a commenter roasted the article’s tone as “belittling,” turning the thread into both a business debate and a writing critique.
Jokes flew about everyone confusing Groq with Grok, plus memes that Nvidia’s grocery list simply reads: “Buy the whole store.” Whether it’s smart strategy or bubble panic, the internet came for the acquisition — and stayed for the flame war
Key Points
- •The article reports Nvidia acquired Groq for $20 billion.
- •Groq develops LPUs (ASIC-based processors) designed to accelerate LLM inference using SRAM for faster memory access.
- •Groq offers GroqCloud, a service providing fast, low-cost, low-energy LPU-powered inference from data centers.
- •Groq primarily supports open-source models (Llama, Mistral, OpenAI’s GPT-OSS), contrasted with higher-quality proprietary models like Anthropic’s Opus 4.5 and Gemini 3 Pro.
- •Real-time use cases such as Formula 1 data analysis are highlighted as strong fits for Groq’s speed-focused approach.