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$216.24
▼ -$2.42(-1.11%)4:32 AM ET - vs previous closeQuote as of Jun 5, 2026, 4:32 AM EDT
Pre-market NASDAQ quote as of Jun 5, 2026, 4:32 AM EDT. Extended-hours prices can sit outside the prior regular-session range.
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Chart
Latest 1D session
Day range position
50% from low
0% = day low, 100% = day high
Vs open
+$2.34 / +1.09%
Intraday follow-through
Opening gap
-2.17%
Open vs previous close
Volume
1.00x avg
167.71M traded
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Derived checks an investor should scan before opening the deeper subroutes.
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Price time means the latest available trade or regular-market close. Other times show when that section was checked or published.
Buy consensus targeting $298.07. Latest catalyst: Structural Risks to Watch For AMD Stock Over the Next 6 Months (Trefis). TECHi maps NVDA to 1 AI leaders and 2 major AI products, making the AI-infrastructure angle visible beside the quote. Attractive growth-adjusted valuation. Next earnings Aug 26
Positive but selective. Strongest input: track record validation (89/100). Main brake: valuation pressure (46/100). Model confidence is 100/100 from 68 of 68 available inputs. Historical progress: 20 Years +62645% total (100/100 progress score); yesterday +1.9%. Rolling price-history validation is 22.8% across 1072 matured horizon scores; full field-by-field accuracy still needs stored daily snapshots.
The strategy layer connects price action with business drivers, financial quality, estimate revisions, and the risks that can change the thesis.
NVIDIA affects people through the accelerated-computing stack behind AI training, inference, scientific simulation, medical imaging, robotics, autonomous systems, creative tools, and developer workflows. The upside is faster deployment of compute-heavy applications; the risk is deeper dependence on a concentrated hardware, software, power, and supply-chain ecosystem.
The durable NVIDIA story is not simply “AI is big and NVIDIA makes chips.” The deeper thesis is that NVIDIA has become a full-stack AI infrastructure provider: GPUs, rack-scale systems, networking, CUDA, inference optimization, and the software layer that customers standardize around.
The quote page should therefore explain what the live chart cannot: why hyperscalers keep buying, why CUDA remains sticky, how Blackwell/Rubin/Feynman create product-cycle visibility, and where custom silicon or customer ROI could weaken the story.
The latest official quarter sharpened that frame. NVIDIA reported Q1 FY2027 revenue of $81.6B, up 85% year over year, with Data Center revenue of $75.2B. That scale makes NVDA less like a normal semiconductor cycle and more like the market’s cleanest public read on AI infrastructure spending.
Custom silicon
Google, Amazon, Microsoft, or Meta route more internal AI workloads to their own chips.
Check: Compare total AI workload growth against NVIDIA share loss. A growing market can offset moderate share erosion.
AMD execution
Large production deployments validate ROCm and improve customer confidence outside NVIDIA.
Check: Track whether AMD wins frontier training, inference, or mostly price-sensitive secondary workloads.
Export controls
China rules tighten or remain restrictive enough to cap high-end accelerator sales.
Check: Separate lost China demand from non-China hyperscaler, enterprise, and sovereign AI demand.
Sizing
Keep position sizing educational and general. Do not let one AI winner silently become the entire portfolio thesis.
Review trigger
Re-check the thesis when hyperscaler capex, Data Center margin, or custom silicon adoption changes direction.
Theme alternatives
AMD, Broadcom, SMH, and SOXX explain other ways to express the AI infrastructure theme without making NVDA the only lever.
| Enterprise value | $5.33T |
| Price / sales | 20.52 |
| Price / book | 27.61 |
| Operating margin | 65.60% |
| Return on assets | 52.70% |
| EPS (TTM) | $6.53 |
| Beta (5Y) | 2.24 |
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5 answers covering the latest TECHi quote snapshot, analyst view, earnings timing, leadership, and sector context.
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