NVDA Stock Today: December 24 Groq $20B Licensing, Ross Joins
The Nvidia Groq deal is the latest sign that AI spend is shifting from training to deployment. Nvidia licensed Groq’s inference technology and hired founder Jonathan Ross, while Groq stays independent and keeps GroqCloud, per multiple reports. For Australian investors, this could speed inference performance and ease HBM constraints. Shares of NVDA trade near their 50‑day average, with neutral momentum readings. We explain the reported US$20 billion figure, what changes for inference chips, and how this could shape NVDA stock risk and reward.
What’s in the Nvidia–Groq arrangement
Reports indicate a non‑exclusive licence to Groq’s inference stack, with Groq retaining GroqCloud, while Jonathan Ross joins Nvidia to help scale next‑gen inference. This points to faster compiler and runtime advances rather than a full platform takeover. The structure keeps Groq independent, reducing integration risk and letting Nvidia move quickly on software paths that improve latency and throughput. source
Coverage citing CNBC pegs the arrangement near US$20 billion, framed as Nvidia’s largest AI move yet. That figure signals the strategic weight of inference, even if the deal is structured as licensing rather than a straight acquisition. Investors should treat the number as directional until official filings land. The market focus is on time‑to‑deployment and developer adoption. source
Why inference now matters more than training
The Nvidia Groq deal aligns with rising inference loads across search, assistants, and enterprise copilots. Inference chips must cut latency, power, and cost per token, not just chase raw FLOPS. Groq’s compiler‑first design and streaming execution could complement Nvidia’s CUDA ecosystem, delivering lower end‑to‑end serving costs. This is where customers are reallocating budgets as models stabilise and usage scales.
Training soaks HBM, creating bottlenecks. Inference can be optimised for memory traffic and batching, easing the HBM squeeze. If Groq’s techniques fold into Nvidia’s stack, datacentres could hit similar throughput with fewer HBM‑heavy accelerators, improving availability and lead times. That supports deployment at hyperscalers and enterprises, while keeping performance per watt high as service‑level agreements tighten.
NVDA stock setup, momentum, and valuation
NVDA recently traded at US$188.61, down 0.32% on the day, with a range of US$186.59 to US$188.91 and a 52‑week high of US$212.19. RSI sits at 57.32, ADX at 13.08 shows no strong trend, and price hugs the upper Bollinger band at US$188.67. ATR of 6.03 implies typical near‑term swings, so position sizing matters around news‑driven moves.
The stock trades at 46.57x EPS with a market cap near US$4.59 trillion, backed by 70% gross margins and robust cash generation. Analyst consensus is Buy, with 55 Buys, 1 Hold, 1 Sell, and a median target of US$232.50. The US$234.73 consensus implies about 24% upside from US$188.61. Price‑to‑book is rich at 38.6x, so execution on inference is key.
What this could mean for Australian investors
For Australians, the Nvidia Groq deal strengthens the case for AI inference exposure via USD assets and, selectively, ASX beneficiaries across data centres and cloud connectivity. Consider hedging currency if needed. Names in Australia tied to AI demand include data‑centre operators, network providers, and power infrastructure. Focus on firms with committed capacity expansions and long‑term contracts supporting AI workloads.
Track developer uptake of Nvidia’s inference software, any published Groq compiler integrations, and hyperscaler announcements. Watch HBM supply commentary, lead times, and pricing. For NVDA, watch free cash flow trends, R&D intensity near 9% of revenue, and the next earnings slated for 25 Feb 2026. Sustained inference wins should support revenue mix, while any slowdown would test the multiple.
Final Thoughts
The Nvidia Groq deal underlines a fast shift from training to inference, where latency, cost per token, and energy use decide winners. A non‑exclusive licence, plus Jonathan Ross joining, suggests Nvidia is buying speed to market rather than reshaping its whole platform. If Groq’s compiler and execution methods improve serving efficiency, Nvidia could relieve HBM pressure and defend share against AMD, Intel, and custom silicon. For Australian investors, the trade‑off is clear: a premium valuation balanced by clear growth lanes in inference. Consider staggered entries near moving averages, maintain currency and position‑size discipline, and watch software adoption, supply dynamics, and hyperscaler demand through 2025. Strong execution would support targets, while delays could compress the multiple.
FAQs
Reports point to a non‑exclusive licensing arrangement where Groq remains independent, keeps GroqCloud, and Jonathan Ross joins Nvidia. Some coverage referenced a US$20 billion figure, but the structure appears centred on access to Groq’s inference stack and leadership talent. Await official details, but the market is treating it as licensing rather than a full acquisition.
Inference can be optimised for memory traffic and batching, reducing HBM intensity versus training. If Groq’s compiler and streaming approach help Nvidia raise throughput per accelerator, customers may need fewer HBM‑heavy units for the same workload, easing supply constraints and improving deployment timelines, particularly for large language model serving.
Technicals are neutral to slightly positive, with RSI near 57 and price close to the upper Bollinger band. Street consensus implies double‑digit upside from current levels. The key catalyst is evidence that inference software gains translate into lower serving costs. Without proof points, valuation sensitivity to macro and competition remains high.
Focus on developer adoption of Nvidia’s inference stack, any public milestones for compiler integration, HBM lead‑time updates, and hyperscaler capex plans. Locally, monitor ASX data‑centre, networking, and power‑grid names tied to AI demand. Manage USD exposure, use staggered entries, and reassess if execution lags or hyperscaler spending moderates.
Disclaimer:
The content shared by Meyka AI PTY LTD is solely for research and informational purposes. Meyka is not a financial advisory service, and the information provided should not be considered investment or trading advice.
