NVIDIA remains the center of AI training and high-end inference demand.
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Price
$203.28
1D change
+0.23%
Market cap
$4.92T
Sector
Technology
Instinct GPUs give hyperscalers a second-source path for AI training and inference.
Price
$503.57
1D change
+1.58%
Market cap
$821.12B
Sector
Technology
ASML is the sole supplier of EUV lithography systems used for the most advanced logic and memory nodes.
Price
$1.7K
1D change
-0.49%
Market cap
$667.96B
Sector
Technology
Most leading AI chips still depend on TSMC's manufacturing and advanced packaging.
Price
$402.30
1D change
+0.99%
Market cap
$2.09T
Sector
Technology
| Metric | NVDA | AMD | ASML | TSM |
|---|---|---|---|---|
| Price | $203.28 | $503.57 | $1.7K | $402.30 |
| 1D Change | +0.23% | +1.58% | -0.49% | +0.99% |
| Market Cap | $4.92T | $821.12B | $667.96B | $2.09T |
| Enterprise Value | $4.87T | $799.91B | $37.29T | $14.04T |
| Trailing P/E | 31.1 | 166.7 | 59.9 | 30.1 |
| Forward P/E | 15.8 | 37.4 | 30.2 | 18.9 |
| PEG Ratio | 0.56x | 1.16x | 2.19x | 1.01x |
| Price / Sales | 19.4 | 21.9 | 18.9 | 0.5 |
| EV / Revenue | 19.2 | 21.4 | 1,055.4 | 3.2 |
| Revenue Growth | 85.2% | 37.8% | 21.3% | 36.0% |
| Earnings Growth | 214.5% | 91.2% | 28.5% | 77.4% |
| Gross Margin | 74.1% | 53.1% | 52.7% | 64.2% |
| Operating Margin | 65.6% | 14.4% | 37.1% | 60.3% |
| Net Margin | 63.0% | 13.4% | 30.1% | 49.9% |
| ROE | 114.3% | 8.1% | 53.9% | 40.0% |
| Free Cash Flow | $46.34B | $7.17B | $8.44B | $739.06B |
| FCF Margin | 18.3% | 19.2% | 23.9% | 16.6% |
| Debt / Equity | 6.55x | 6.00x | 9.09x | 0.15x |
| Current Ratio | 3.44x | 2.73x | 1.33x | 2.46x |
| Dividend Yield | 0.49% | 0.00% | 0.73% | 0.95% |
| Next Earnings | Aug 26, 2026 | Aug 04, 2026 | Oct 14, 2026 | Oct 15, 2026 |
| Quarterly Revenue | $81.61B | $10.25B | $9.33B | $1.27T |
| Revenue QoQ | +19.8% | -0.2% | +6.4% | +12.0% |
| Quarterly Net Income | $58.32B | $1.38B | $2.92B | $706.56B |
| Net Income QoQ | +35.8% | -8.5% | +5.8% | +23.4% |
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.