#NvidiaPerplexityBet
About NvidiaPerplexityBet
Nvidia may join Perplexity's new funding round at a valuation above $30B, over 50% higher than the prior ~$20B; its investment size is unknown. AI servers with Nvidia's next-gen chips may cost over 15% more next year. Raising hardware prices while investing in model and app companies moves Nvidia beyond chip supply toward organizing AI capital. Can this build real demand and long-term revenue, or make GPU sales more reliant on downstream financing and deepen circular-investment concerns?
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NvidiaPerplexityBet Suositut postaukset
Chipmaker @nvidia reportedly considered licensing @perplexity_ai’s tech and hiring staff. Now @theinformation says Nvidia may lead a multibillion-dollar investment at a valuation above $30B.
Perplexity’s annualized revenue reportedly now exceeds $750M.#BTCETFInflowsSurge #ETHTests2500 #OKXOutcomeF1TI15Recap
NVIDIA’s strategy: commoditize intelligence
NVIDIA made three large acquisitions / investments in the space of a few days: Hugging Face, Poolside and Perplexity. (Two rumored, but seem likely)
All three target the same goal: help build a robust open source ecosystem as a counterweight to OpenAI and Anthropic.
Hugging Face is the distribution layer — the GitHub of open-source AI, where models, datasets and tooling live.
Poolside is the model-building layer — NVIDIA is paying $6B to license its “Model Factory” technology, while investing another $1B in the company. The obvious application is accelerating NVIDIA’s own Nemotron/open-weight model efforts.
Perplexity is the application layer — a scaled consumer product that proves open models can support products competing directly with the closed-model labs. NVIDIA is reportedly discussing another investment at a 30b+ valuation.
Put them together and the strategy becomes clearer:
Poolside Model Factory → Models → Hugging Face → developers → applications like Perplexity → more demand for NVIDIA GPUs.
NVIDIA doesn’t need to beat OpenAI or Anthropic itself. It needs to make sure there are thousands of credible alternatives to them.
Because a world dominated by a handful of vertically integrated closed-model companies is ultimately bad for the company selling the picks and shovels.
NVIDIA wants intelligence to commoditize.
Compute is where it wants the scarcity to remain.
PS: One of the biggest implications of this is that open source shifts the economics to the inference vendors (who are also nvda customers) from the model labs (who are also customers).
$NVDA is moving deeper into the AI factory buildout with a strategic investment in Lancium.
The partnership will deploy its full-stack platform across Lancium’s 15+ GW portfolio giving it another direct channel into one of the largest planned AI infrastructure pipelines.
$NVDA, LANCIUM PARTNER ACROSS 15+ GW AI DATA CENTER PIPELINE
NVIDIA has made a strategic investment in Lancium and will deploy its full-stack AI factory platform across the company’s power-secured campus portfolio.
Lancium currently has 4 GW of capacity under lease and more than 15 GW of powered land in development.
The partnership will use NVIDIA DSX designs to speed deployments and improve power efficiency, including DSX MaxLPS, which NVIDIA says can support up to 40% more GPUs within the same power budget.
The deal gives NVIDIA customers access to gigawatt-scale, power-ready sites as AI infrastructure demand continues to shift toward securing power and capacity years in advance.
