Nvidia to buy assets from Groq for $20B cash

Original Article ↗ Hacker News Discussion ↗

Deal structure and what’s actually being bought

  • Initial headline framed it as an acquisition of Groq for $20B in cash; several commenters point out the official release describes:
    • A non‑exclusive inference technology licensing deal.
    • Key executives and some staff moving to Nvidia.
    • Groq continuing as an “independent company” with a new CEO and GroqCloud “continuing to operate.”
  • Many see this as a de‑facto acquihire + IP transfer structured to dodge formal merger review, not a classic M&A buyout.
  • There’s confusion over how GroqCloud can run if Nvidia “owns the hardware”; later comments clarify Nvidia gets a license, not exclusive rights.

Competition, antitrust, and politics

  • Strong concern that one of the few credible non‑GPU inference architectures is being neutralized, further entrenching Nvidia’s dominance.
  • Repeated questions how this isn’t an antitrust case; responses range from “US antitrust is dead / unenforced” to “structured as licensing to skirt scrutiny.”
  • Some highlight recent investors (including politically connected figures) and read the price as effectively a political payoff; others call that conspiracy‑ish but note the optics.
  • A minority argue Groq’s market share is tiny, so regulators may see no case.

Strategic and technical rationale (disputed)

  • Pro‑deal view: Nvidia needs an ASIC/inference story (LPU vs TPU) as GPUs hit power/scale limits; buying Groq accelerates having an SRAM‑based, ultra‑fast inference product and key interconnect IP.
  • Skeptical view: at ~40× target revenue and 3× the recent valuation, this doesn’t meaningfully change Nvidia’s real competitive landscape (Google TPU, Amazon Trainium, AMD, etc.) and looks mostly like paying to eliminate future competition.
  • Some think Groq’s HBM‑free, SRAM‑heavy approach is only attractive because of current memory constraints.

Ecosystem, open source, and remaining competitors

  • Many are “genuinely sad” to lose Groq as an independent fast‑inference option; some immediately stopped using its API.
  • Others hope competitors like Cerebras, Tenstorrent, various Chinese vendors, and smaller stealth players will fill the gap.
  • Debate on open source:
    • One camp: Groq + fast inference were key enablers making open models more viable against closed LLMs; this weakens that force.
    • Another camp: Nvidia actually benefits from more open‑source models (they all need GPUs); this is about diversifying Nvidia’s own stack, not suppressing open source.

Employees, investors, and incentives

  • Big focus on who actually gets the $20B:
    • Some expect investors and senior leadership to capture most of the upside, with rank‑and‑file equity/RSUs at risk in a “not‑an‑acquisition” structure.
    • Others suggest the license fee could be distributed as a dividend/buyback, potentially paying out common shareholders too, but this is speculative and unclear.
  • Several see this as part of a broader trend: acquirers buying assets/teams instead of companies, leaving early employees with near‑worthless options and weakening the appeal of startup equity.

Overall sentiment

  • Majority tone: negative—frustration at consolidation, fear of slower innovation and higher prices, calls for stronger antitrust enforcement.
  • Minority: pragmatic—this is exactly what a rational, cash‑rich incumbent should do in an AI bubble; it may even accelerate deployment of Groq‑style tech at scale.