December 17, 2025 — NVIDIA Corporation (NASDAQ: NVDA) is back in the spotlight as investors weigh two powerful forces moving the AI hardware market in opposite directions: continued expansion in AI infrastructure spending and accelerating competition from alternative chips and geopolitics.
Early Wednesday, NVDA traded around $177.72, up about 0.7% on the session after opening near $176.12, with an intraday range roughly $176.48–$178.34.
Below is what’s driving NVIDIA stock today, what analysts are forecasting for 2026, and the key risks that could determine whether NVDA breaks out—or stays stuck in consolidation.
NVDA stock price today: what the market is signaling
NVIDIA shares are modestly higher in early trading on December 17, but the day’s most important signals aren’t just in the tape. They’re in the direction of AI infrastructure:
- Will the largest AI model builders keep buying NVIDIA GPUs at the same pace?
- Will “good enough” alternatives—custom chips, domestic China options, and open standards—take meaningful share?
- Can NVIDIA expand its moat beyond silicon and deeper into software and ecosystem control?
Today’s news flow touches all three.
The biggest NVDA headline today: Amazon’s reported $10B+ OpenAI talks and the “Trainium question”
One of the most market-relevant stories for NVIDIA on December 17 centers on OpenAI’s infrastructure strategy—and whether it becomes less NVIDIA-dependent over time.
Reuters reported that Amazon is in talks to invest about $10 billion in OpenAI, with discussions tied to OpenAI potentially using more of Amazon’s Trainium AI chips. [1]
The Financial Times similarly reported early-stage talks for an investment over $10 billion, framing it as part of OpenAI’s push to diversify infrastructure and chip supply. [2]
Why this matters for NVIDIA stock
NVIDIA’s market leadership has been powered by a simple reality: the world’s biggest AI spenders (cloud platforms, hyperscalers, model labs, and enterprises) have overwhelmingly built around CUDA and NVIDIA GPUs. When a buyer as important as OpenAI tests alternatives—especially via a hyperscaler’s in-house chip program—that introduces a new question into NVDA valuation:
Is GPU demand growing so fast that NVIDIA can dominate even as alternatives expand, or do alternatives eventually cap NVIDIA’s upside multiple?
It’s not necessarily a “loss” story. Even if OpenAI adopts Trainium for some workloads, NVIDIA GPUs can remain foundational across training, inference, and deployment—especially where performance, tooling, and time-to-market matter most. But for investors, the direction of travel (more heterogeneous compute, more custom silicon) can affect how much growth gets priced into NVDA.
China’s AI-chip push heats up: MetaX IPO surge underscores competitive and regulatory pressure on NVDA
Another major NVIDIA-adjacent story today is the speed and intensity of China’s domestic AI chip buildout.
Reuters reported that MetaX Integrated Circuits surged roughly 700% in its Shanghai debut, highlighting strong investor appetite as China pushes for AI-chip self-sufficiency. [3]
The same report noted several key data points investors are watching closely:
- MetaX raised about $600 million and was “wildly oversubscribed,” reflecting speculative heat in the sector. [4]
- MetaX currently holds about 1% of China’s AI chip market and expects rapid growth, aiming for profitability next year. [5]
- China’s AI chip market is projected to reach $189 billion by 2029, with other domestic players preparing IPOs. [6]
The NVDA angle: share risk + policy risk
For NVIDIA stock, China remains a complicated mix of demand, restrictions, and long-term strategic uncertainty:
- In the near term, China demand can still be strong where exports are allowed.
- Over the long term, China is clearly funding alternatives and building a domestic supply chain designed to reduce reliance on U.S. leaders like NVIDIA.
Reuters also reported separately that China has pursued a highly secretive, state-backed effort to advance chipmaking independence—an initiative described as akin to a “Manhattan Project” for semiconductor capability. [7]
Even if such efforts take years to fully materialize into competitive, leading-edge output, they reinforce the long-run strategic objective: China wants to control its AI compute stack end-to-end.
H200 export dynamics add another layer of uncertainty for NVIDIA
On the demand side, China is still important enough that changes in export policy can move assumptions about NVIDIA’s revenue mix.
Reuters reported that NVIDIA has considered increasing H200 chip output after unexpectedly strong demand from Chinese tech firms, following a U.S. decision allowing exports with a 25% fee. [8]
But the same environment also introduces risk: approvals, supply prioritization, and shifting government policies can all change the realizable opportunity.
For investors, the takeaway is that China exposure can act like an “accordion” in forecasts—expanding on favorable policy, contracting quickly on restrictions or domestic substitution.
AI bubble fears vs. the “capex reality”: why this debate keeps returning to NVDA
NVIDIA is often treated as the market’s real-time referendum on the AI buildout. So when “AI bubble” concerns reappear, they usually show up first in NVDA’s multiple.
A Barron’s summary of UBS commentary said UBS does not see evidence of an AI investment bubble, while projecting global AI capex rising from $423 billion in 2025 to $571 billion in 2026, and estimating AI market revenue could reach $3.1 trillion by 2030. [9]
A separate recap citing UBS figures echoed those same capex and market-size estimates. [10]
Why the market still worries
Even if AI capex grows, investors still ask:
- How quickly do AI products convert into durable profits?
- Do model builders shift from “buy everything” to “optimize everything,” reducing GPU intensity?
- Does the infrastructure mix shift toward custom silicon or cheaper alternatives?
That’s the tug-of-war inside NVDA’s valuation today: structural demand vs. marginal substitution.
NVIDIA’s moat isn’t just chips: SchedMD (Slurm) acquisition and the open-source strategy
While markets debate chip alternatives, NVIDIA has been making moves designed to deepen its lock-in at the platform level.
NVIDIA acquires SchedMD, the company behind Slurm
Reuters reported NVIDIA acquired SchedMD, known for Slurm, an open-source workload manager widely used to schedule large compute jobs in data centers. [11]
NVIDIA also stated it would continue distributing the software on an open-source basis. [12]
NVIDIA’s own announcement described SchedMD as the leading developer of Slurm, positioning the deal as a way to strengthen the open-source ecosystem for HPC and AI. [13]
Why it matters for NVDA stock: Slurm is deeply embedded in how large clusters run. Owning influence over a key orchestration layer helps NVIDIA defend its “full-stack” story—where customers buy into more than GPUs: they buy into deployment patterns, tooling, and operational muscle memory.
NVIDIA debuts Nemotron 3 family of open models
NVIDIA also announced Nemotron 3, a family of open models (Nano, Super, Ultra) aimed at agentic AI development, emphasizing throughput and efficiency improvements. [14]
This strategy isn’t charity—it’s ecosystem economics. Open models, libraries, and tooling can increase developer adoption and make NVIDIA the default platform even when hardware choices expand.
NVIDIA–OpenAI partnership: a long-run demand signal investors shouldn’t ignore
Today’s Amazon/OpenAI Trainium chatter is important—but it sits alongside a separate, very large NVIDIA–OpenAI infrastructure roadmap already on the table.
NVIDIA has previously announced a strategic partnership with OpenAI to deploy at least 10 gigawatts of NVIDIA systems for OpenAI’s next-generation AI infrastructure. [15]
That announcement also stated NVIDIA intends to invest up to $100 billion progressively as deployments occur. [16]
For long-term NVDA investors, this is part of the “visibility” argument: demand is not just speculative; it’s being structured into multi-year infrastructure commitments.
NVDA stock forecast: what Wall Street expects for 2026
Analyst forecasts remain broadly constructive, with notable differences in target levels depending on assumptions about competition, China, and the durability of hyperscaler capex.
Consensus targets imply meaningful upside from current levels
MarketBeat’s analyst aggregation shows an average 12-month price target around $258.65, with a high of $352 and a low of $205, implying roughly mid-40% upside from around $177.72. [17]
Investing.com’s consensus estimates similarly list an average target around $250.93, high $352, and low $140, and characterize overall sentiment as “Strong Buy.” [18]
Key bullish pillar: BofA says NVIDIA remains a generation ahead
A Bank of America note summarized by Investing.com reiterated a Buy rating and a $275 price target, arguing NVIDIA GPUs remain “a full generation ahead,” with Blackwell described as 10x–15x better generation-over-generation and “Blackwell-trained” LLMs expected to arrive in early 2026. [19]
The same note said NVIDIA’s next-gen Vera Rubin platform remains on schedule for the second half of 2026 and highlighted what it called demand and supply visibility into a $500 billion sales outlook across 2025–2026. [20]
The high-end bull case: Evercore’s $352 target
Investing.com reported Evercore ISI raised its price target to $352 while maintaining an outperform stance, citing reaccelerating growth and improving availability. [21]
What to make of it: The Street’s upper-end targets generally depend on three things staying true at once:
- AI capex keeps growing,
- NVIDIA sustains premium share in the most performance-sensitive workloads, and
- product ramps (Blackwell → Rubin) arrive on time and in volume.
NVIDIA fundamentals check: last earnings, guidance, and what’s next
The most recent official financial snapshot still supports the “demand is real” narrative.
In its Q3 fiscal 2026 release (quarter ended Oct. 26, 2025), NVIDIA reported:
- Revenue: $57.0 billion (up 22% QoQ, up 62% YoY) [22]
- Data Center revenue: $51.2 billion (up 25% QoQ, up 66% YoY) [23]
- GAAP EPS: $1.30 [24]
For the next quarter (Q4 fiscal 2026), NVIDIA guided:
- Revenue of $65.0 billion ± 2% [25]
NVIDIA also disclosed capital return details including:
- $37.0 billion returned via buybacks and dividends over the first nine months of fiscal 2026
- $62.2 billion remaining under repurchase authorization
- A $0.01 quarterly dividend payable Dec. 26, 2025 [26]
Next major date for NVDA investors: Feb. 25, 2026
NVIDIA’s investor events calendar lists February 25, 2026 for NVIDIA’s 4th Quarter FY26 financial results. [27]
What to watch next for NVIDIA stock
If you’re tracking NVDA into year-end and early 2026, these are the pressure points likely to matter most:
1) OpenAI’s infrastructure choices and broader hyperscaler mix shifts
Amazon’s Trainium push and OpenAI’s reported willingness to expand beyond NVIDIA hardware raises the broader question: how quickly does heterogeneous compute adoption scale? [28]
2) China: demand today vs. domestic substitution tomorrow
MetaX’s IPO surge is a vivid reminder that China is funding alternatives aggressively—even if there remains a technology gap today. [29]
Meanwhile, policy-driven uncertainty around which chips can be sold, and in what quantities, remains a recurring NVDA narrative. [30]
3) The platform war: software, orchestration, and open standards
NVIDIA’s SchedMD acquisition and Nemotron 3 release are signals that the company is working to stay essential even if the hardware layer becomes more competitive. [31]
In parallel, Reuters Breakingviews highlighted the growing relevance of open-standard chips (including RISC‑V) and noted NVIDIA’s plan to support RISC‑V on CUDA—another data point in the “ecosystem positioning” battle. [32]
4) The “AI capex durability” debate
As UBS-framed capex expectations rise, the market will demand clearer proof that AI spend is translating into sustainable returns—not just bigger clusters. [33]
Bottom line on NVDA stock on Dec. 17, 2025
NVIDIA stock is modestly higher today, but the bigger story is strategic:
- The demand engine (AI infrastructure buildout) still looks powerful, with multi-year deployments and guidance supporting scale. [34]
- The competitive landscape is clearly intensifying—through hyperscaler custom chips (like Trainium), China-backed challengers, and shifts toward heterogeneous compute. [35]
- NVIDIA is responding by strengthening its full-stack moat, from Slurm scheduling to open models, aiming to remain the default platform even in a more mixed-hardware world. [36]
References
1. www.reuters.com, 2. www.ft.com, 3. www.reuters.com, 4. www.reuters.com, 5. www.reuters.com, 6. www.reuters.com, 7. www.reuters.com, 8. www.reuters.com, 9. www.barrons.com, 10. www.gurufocus.com, 11. www.reuters.com, 12. www.reuters.com, 13. blogs.nvidia.com, 14. investor.nvidia.com, 15. nvidianews.nvidia.com, 16. nvidianews.nvidia.com, 17. www.marketbeat.com, 18. www.investing.com, 19. www.investing.com, 20. www.investing.com, 21. www.investing.com, 22. investor.nvidia.com, 23. investor.nvidia.com, 24. investor.nvidia.com, 25. investor.nvidia.com, 26. investor.nvidia.com, 27. investor.nvidia.com, 28. www.reuters.com, 29. www.reuters.com, 30. www.reuters.com, 31. www.reuters.com, 32. www.reuters.com, 33. www.barrons.com, 34. investor.nvidia.com, 35. www.reuters.com, 36. www.reuters.com
