NVIDIA remains the center of AI training and high-end inference demand.
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Price
$186.64
1D change
+2.78%
Market cap
$4.51T
Sector
Technology
Instinct GPUs give hyperscalers a second-source path for AI training and inference.
Price
$449.04
1D change
+11.04%
Market cap
$736.46B
Sector
Technology
ASML is the sole supplier of EUV lithography systems used for the most advanced logic and memory nodes.
Price
$1.4K
1D change
+5.02%
Market cap
$549.12B
Sector
Technology
Most leading AI chips still depend on TSMC's manufacturing and advanced packaging.
Price
$375.44
1D change
+6.33%
Market cap
$1.95T
Sector
Technology
| Metric | NVDA | AMD | ASML | TSM |
|---|---|---|---|---|
| Price | $186.64 | $449.04 | $1.4K | $375.44 |
| 1D Change | +2.78% | +11.04% | +5.02% | +6.33% |
| Market Cap | $4.51T | $736.46B | $549.12B | $1.95T |
| Enterprise Value | $4.47T | $729.90B | $30.31T | $12.38T |
| Trailing P/E | 23.6 | 95.9 | 35.1 | 24.3 |
| Forward P/E | 11.7 | 25.5 | 22.5 | 16.1 |
| PEG Ratio | 0.23x | 0.40x | 0.74x | 0.68x |
| Price / Sales | 14.9 | 16.2 | 13.9 | 0.4 |
| EV / Revenue | 14.8 | 16.1 | 767.9 | 2.5 |
| Revenue Growth | 105.9% | 44.7% | 55.2% | 50.9% |
| Earnings Growth | 127.8% | 93.8% | 135.9% | 68.7% |
| Gross Margin | 74.7% | 56.0% | 54.3% | 65.8% |
| Operating Margin | 66.2% | 21.2% | 44.4% | 58.7% |
| Net Margin | 63.7% | 16.8% | 34.1% | 51.1% |
| ROE | 117.2% | 12.0% | 65.6% | 41.9% |
| Free Cash Flow | $41.81B | $7.36B | $10.37B | $1.20T |
| FCF Margin | 13.8% | 16.2% | 26.3% | 24.3% |
| Debt / Equity | 0.17x | 0.13x | 8.90x | 0.12x |
| Current Ratio | 4.59x | 2.73x | 1.49x | 2.50x |
| Dividend Yield | 0.54% | 0.00% | 0.59% | 1.18% |
| Next Earnings | Nov 17, 2026 | Feb 02, 2027 | Jan 27, 2027 | Jan 14, 2027 |
| Quarterly Revenue | $96.22B | $13.38B | $11.66B | $1.49T |
| Revenue QoQ | +17.9% | +16.0% | +25.0% | +17.6% |
| Quarterly Net Income | $59.69B | $2.43B | $4.96B | $763.06B |
| Net Income QoQ | +2.3% | +5.7% | +70.0% | +8.0% |
NVDA thesis lens
AI compute platform
Why it could benefit
- NVIDIA remains the center of AI training and high-end inference demand.
- Its stack includes chips, networking, systems, CUDA, and software libraries, not just GPUs.
- As models get larger and enterprises move into production, full-stack control becomes more valuable.
Moat / edge
- CUDA ecosystem and developer lock-in.
- Leading performance in accelerated computing.
- Integrated platform spanning silicon, interconnect, and software.
What to watch
- Supply-demand balance for each new architecture cycle.
- Mix shift between hyperscalers and enterprise customers.
- Competition from custom silicon and AMD.
Key risks
- Customer concentration and product-transition execution matter a lot.
- Any sharp slowdown in capex could compress expectations quickly.
AMD thesis lens
GPU/CPU AI accelerator challenger
Why it could benefit
- Instinct GPUs give hyperscalers a second-source path for AI training and inference.
- EPYC CPUs and adaptive compute help AMD participate across the AI server bill of materials.
- If open accelerator ecosystems broaden, AMD can gain share from customers avoiding single-vendor dependence.
Moat / edge
- High-performance CPU franchise and growing GPU roadmap.
- Deep relationships with hyperscalers, OEMs, and enterprise server buyers.
- Chiplet design capability and manufacturing partnership with TSMC.
What to watch
- Instinct shipment ramp and software maturity.
- Gross margin mix between CPUs, GPUs, gaming, and embedded.
- Cloud customer adoption versus Nvidia alternatives.
Key risks
- Nvidia's software ecosystem remains the hardest competitive hurdle.
- AI GPU demand can be lumpy if customer qualification slips.
ASML thesis lens
EUV lithography chokepoint
Why it could benefit
- ASML is the sole supplier of EUV lithography systems used for the most advanced logic and memory nodes.
- AI compute demand raises the need for leading-edge wafer capacity.
- Memory ramps such as advanced DRAM and HBM also pull on lithography intensity.
Moat / edge
- Unique EUV technology stack with deep supplier specialization.
- Entrenched customer relationships with leading-edge foundries and memory makers.
- Long development cycles make displacement extremely difficult.
What to watch
- EUV and High NA EUV order trends.
- China restrictions and shipment timing.
- Foundry and memory capex cycles.
Key risks
- Export controls can limit sales into key regions.
- Semicap cycles can create long drawdowns despite strong long-term positioning.
TSM thesis lens
Advanced semiconductor manufacturing
Why it could benefit
- Most leading AI chips still depend on TSMC's manufacturing and advanced packaging.
- As AI complexity rises, foundry leadership in yield, scale, and packaging matters more.
- TSMC is a cleaner way to own the ecosystem rather than one end-market winner.
Moat / edge
- Leading-edge process technology.
- Manufacturing scale and execution track record.
- Hard-to-replicate ecosystem trust with top chip designers.
What to watch
- Capacity additions in advanced nodes and CoWoS-type packaging.
- Geographic expansion and margin preservation.
- Mix between smartphone, HPC, and AI demand.
Key risks
- Geopolitical risk is always part of the TSMC thesis.
- Large customer concentration can amplify cycle swings.