December 17, 2025 — NVIDIA Corporation (NASDAQ: NVDA) is trading around the $177–$178 area heading into Wednesday’s session, after closing Tuesday, Dec. 16 at $177.72. [1]
That price level—steady, but not euphoric—captures the mood around Nvidia right now: investors are still treating it as the core “picks-and-shovels” winner of the AI boom, while also wrestling with three big questions that keep showing up in today’s reporting and analysis:
- Is the AI trade becoming a bubble—or just entering the messy, normal phase of scaling?
- Can Nvidia deepen its moat by expanding beyond chips into open-source software and models?
- How much do U.S.–China chip rules (and China’s local alternatives) cap the next leg of growth?
Here’s what’s driving Nvidia stock coverage on December 17, 2025, plus the forecasts and analyst arguments shaping sentiment into 2026.
NVDA price action: steady near $178 after a choppy stretch for AI leaders
Nvidia ended Tuesday at $177.72 (up about 0.8%) with heavy volume, and it was indicated slightly higher in premarket trading early Wednesday. [2]
The bigger story is not a single day’s candle—it’s the market’s ongoing tug-of-war between:
- AI infrastructure optimism (massive compute demand still ramping), and
- valuation discipline (investors asking harder questions about return on AI capex).
That caution is visible across U.S. equities more broadly: Reuters reported stock index futures edging higher Wednesday as investors waited for additional economic signals and Fed commentary, while “concerns over tech valuations” continue to influence sector rotation. [3]
The AI bubble debate is back—and UBS is pushing back on the bubble narrative
A major theme in Nvidia stock commentary today is whether AI spending is overheating. Barron’s framed Nvidia as “walking a fine line” between AI bubble fears and fundamental demand, noting Nvidia shares finished higher even as the debate stayed loud. [4]
A key counterargument highlighted in that coverage: UBS strategists don’t see classic bubble conditions yet, because spending is still broadening beyond early experiments toward enterprise, industrial, and workflow deployments.
Today’s reporting cited UBS estimates that:
- Global AI capex could rise from ~$423B in 2025 to ~$571B in 2026
- AI market revenue could reach ~$3.1T by 2030 (implying ~30% annual growth) [5]
For Nvidia investors, these projections matter because they reinforce the idea that demand isn’t just “chatbots and hype”—it’s tied to a multi-year buildout of data centers, networking, power infrastructure, and software stacks that keep models running in the real world.
Nvidia’s open-source strategy: Slurm (SchedMD) + Nemotron 3 models
While the bubble debate grabs headlines, Nvidia’s product and ecosystem moves are arguably the more important “tell” for long-term investors: the company is trying to make itself harder to displace by owning more of what happens around the GPU.
1) Nvidia buys SchedMD, the company behind Slurm
This week Nvidia announced it acquired SchedMD, the developer of Slurm, a widely used open-source workload manager for high-performance computing (HPC) and AI clusters. Reuters reported Nvidia is positioning the deal as part of a broader push into open-source technology while competition intensifies. [6]
Nvidia’s own announcement emphasized two details investors tend to care about:
- Nvidia will continue developing and distributing Slurm as open-source and vendor-neutral
- Slurm is deeply embedded in major compute environments (Nvidia noted Slurm is used in more than half of the top 10 and top 100 systems in the TOP500 supercomputer list) [7]
Why this matters for NVDA stock:
Slurm sits at the nerve center of large clusters: it decides which jobs run where, when, and with what resources. By aligning closely with Slurm’s ecosystem while keeping it vendor-neutral, Nvidia can reduce friction for enterprises building GPU-heavy clusters—without triggering the backlash that comes from “closing” open infrastructure.
2) Nvidia debuts Nemotron 3 open models aimed at “agentic AI”
Nvidia also launched the Nemotron 3 family of open models, positioning them for the next software wave: AI agents that coordinate tools, workflows, and other models. Nvidia’s press materials describe Nemotron 3 as an “open model stack” designed to support transparent, efficient, specialized agentic AI development. [8]
Key details Nvidia disclosed include:
- Three model sizes: Nano, Super, and Ultra
- Nemotron 3 Nano is described as a 30B-parameter model (activating fewer parameters per token via a mixture-of-experts design)
- Nvidia claims up to 4x higher throughput versus Nemotron 2 Nano and a 1-million-token context window for long tasks [9]
Reuters added that Nvidia is releasing these open models as Chinese open-source offerings gain traction globally—while some U.S. organizations restrict Chinese models for security reasons, potentially creating demand for “trusted” open alternatives from a U.S. vendor. [10]
The investor angle:
Nvidia is signaling that it doesn’t just want to sell GPUs to companies building agents—it wants to help define the “default” tooling layer. The more developers standardize on Nvidia’s models, libraries, and scheduling infrastructure, the more Nvidia can reinforce demand for its hardware and systems.
China is still a major NVDA wildcard: H200 export rules and the rise of local rivals
Nvidia’s China narrative in late 2025 is complicated—and investors are treating it as both a potential catalyst and a risk.
The U.S. says H200 exports can resume—with a 25% fee
Reuters reported earlier this month that the United States will allow Nvidia’s H200 processors (a top-tier AI chip line, but not Nvidia’s newest) to be exported to China, with a 25% fee tied to those sales. Reuters also noted Trump said the newest “Blackwell” chips and the next-generation “Rubin” line were not part of the deal. [11]
Beijing may still limit access—even if Washington approves
In a follow-up, Reuters reported the Financial Times saying Beijing could restrict access to H200s despite U.S. approval, adding uncertainty about how much incremental revenue Nvidia can actually capture from China. [12]
Nvidia reportedly evaluates increasing H200 capacity due to China demand
Adding another twist: Reuters reported Nvidia told Chinese clients it was evaluating whether to add production capacity for H200 chips after demand exceeded current output—while also stating it would manage supply to avoid impacting U.S. customers. The report described strong interest from major Chinese firms, while noting Chinese government approval remained uncertain. [13]
Bottom line: China demand can be real and still be hard to monetize at scale, because the bottleneck can shift from customers → policy → logistics → licensing.
China’s homegrown push is accelerating—and today’s MetaX IPO was a vivid signal
On Dec. 17, Reuters covered the Shanghai debut of MetaX Integrated Circuits, which surged roughly 700% on its first day—an eye-catching example of how aggressively China is funding domestic AI chip capacity to reduce reliance on Nvidia and AMD. [14]
Reuters also cited Frost & Sullivan forecasting China’s AI chip sales could reach $189B by 2029 (vs $54B in 2026), underscoring the size of the prize—and why local champions are attracting capital. [15]
For Nvidia shareholders, this doesn’t mean “Nvidia is doomed in China.” It does mean China is trying to ensure that, over time, Nvidia becomes less central to the country’s AI trajectory—especially for state-linked infrastructure.
Forecasts and analyst views on Dec. 17: bullish targets, but the reasoning is evolving
Today’s NVDA discourse is less about “will AI exist?” and more about how fast spending converts into revenue and durable margins—and whether consensus forecasts are still too conservative.
“Analysts may still be underestimating Nvidia,” argues Nasdaq.com analysis
A widely circulated analysis published today on Nasdaq.com argues Wall Street may still be underestimating Nvidia’s long-term growth potential, pointing to demand visibility and product cadence. [16]
Notable claims and figures in that analysis include:
- Order visibility of $500B for Blackwell and Rubin systems from the start of 2025 through the end of 2026
- About $150B of that already shipped
- A stated consensus target price around $256.95, described as more than 45% above the Dec. 16 close [17]
It also highlighted Nvidia’s faster release cycle and roadmap references (Blackwell / Blackwell Ultra, Rubin, and beyond), arguing that more frequent platform refreshes can pull forward demand. [18]
Another “soft” consensus check: MarketBeat’s current average target in the high $250s
MarketBeat’s analyst aggregation currently lists an average 12‑month NVDA price target around $258.65, with targets ranging higher and lower depending on the firm. [19]
This aligns with a broader theme across today’s coverage: many analysts still see meaningful upside from the current ~$178 level, but the debate is increasingly about how much of the good news is already priced in.
The bear case isn’t dead—it’s just getting more specific
Even among NVDA bulls, the more cautious arguments tend to cluster around:
- hyperscalers optimizing spend (or shifting part of compute to custom silicon),
- competitive pressure from AMD and custom accelerators,
- and policy friction in China.
That’s not “AI is fake” skepticism. It’s a more surgical question: does Nvidia’s current valuation require everything to go right at once?
What to watch next for NVIDIA stock
1) Next earnings date: February 25, 2026 (Q4 FY26 results)
Nvidia’s investor relations calendar lists February 25, 2026 for “NVIDIA 4th Quarter FY26 Financial Results.” [20]
Between now and then, investors will likely focus on signals around:
- Blackwell and next-gen system ramps,
- gross margin trajectory (especially if product mix shifts),
- and data center demand concentration.
2) The last reported quarter still looms large in expectations
In its most recent quarterly results release (Q3 FY26, ended Oct. 26, 2025), Nvidia reported:
- Record revenue of $57.0B
- Record Data Center revenue of $51.2B [21]
Those numbers help explain why the stock is still treated as the “default” AI infrastructure bet—even as valuation nerves periodically flare up.
3) China policy headlines can move NVDA quickly
Given the interplay of U.S. export rules, potential fees, and Beijing’s responses, China-related news can swing sentiment abruptly. Reuters’ reporting in December showed how quickly “approval” headlines can be complicated by “access limits” and local policy considerations. [22]
4) Rising competition is real—but so is the ecosystem advantage
Today’s MetaX coverage is a reminder that competitors can gain momentum—especially with government backing. [23]
But Nvidia’s SchedMD and Nemotron moves show it’s also competing on the “full stack”: chips + systems + software + models. [24]
The takeaway: NVDA’s story is shifting from “AI boom” to “AI buildout”
As of Dec. 17, 2025, Nvidia stock sits at an interesting intersection:
- The market still views Nvidia as essential to AI infrastructure,
- but it’s no longer a “one-way trade,” because investors are demanding proof that AI spending produces sustainable returns (not just bigger capex budgets).
The most important thing to notice in today’s newsflow isn’t a single price tick. It’s that Nvidia is actively trying to widen its moat—through open-source infrastructure (Slurm) and open models (Nemotron 3)—at the same time that geopolitics and China’s domestic chip push introduce uncertainty at the margin. [25]
That combination—strong fundamentals, noisy narratives, real policy risk—is exactly why NVDA remains one of the most covered (and most contested) stocks in the market heading into 2026.
References
1. stockanalysis.com, 2. stockanalysis.com, 3. www.reuters.com, 4. www.barrons.com, 5. www.barrons.com, 6. www.reuters.com, 7. blogs.nvidia.com, 8. nvidianews.nvidia.com, 9. nvidianews.nvidia.com, 10. www.reuters.com, 11. www.reuters.com, 12. www.reuters.com, 13. www.reuters.com, 14. www.reuters.com, 15. www.reuters.com, 16. www.nasdaq.com, 17. www.nasdaq.com, 18. www.nasdaq.com, 19. www.marketbeat.com, 20. investor.nvidia.com, 21. investor.nvidia.com, 22. www.reuters.com, 23. www.reuters.com, 24. blogs.nvidia.com, 25. blogs.nvidia.com
