QCOM vs NVDA Stock Comparison: AI Score, Valuation, Performance and Upside
Qualcomm and Nvidia are both AI semiconductor companies, but in very different markets. Qualcomm dominates mobile AI — the on-device neural processing in smartphones and PCs. Nvidia dominates data center AI — the cloud-based GPU clusters training and running large language models. These are largely non-overlapping markets with little direct competition; Qualcomm's Snapdragon competes for mobile edge AI while Nvidia's H100/B200 wins data center AI training.
QCOM vs NVDA is mobile semiconductor leader with 5G patent royalties, Snapdragon AI SoCs, and emerging PC/automotive expansion (Qualcomm) versus the dominant AI training GPU platform with CUDA software lock-in and $40B+ quarterly data center revenue (Nvidia) — mobile edge AI vs cloud data center AI in largely separate markets.
NVDA holds the edge across 4 of 5 key metrics in this comparison. QCOM has delivered stronger 1-year price return (+46.39% vs +46.19%), though NVDA trades at the lower forward P/E (16.12x vs 19.85x). NVDA leads on both revenue growth (85.20%) and operating margin (65.60%), suggesting a stronger fundamental setup on both dimensions. Analyst consensus implies meaningfully more upside for NVDA (+45.69%) than for QCOM (-14.75%).
- →prefer the global mobile chip leader with 5G patent royalty income as a durable, competitively-protected revenue stream irrespective of chip market share battles
- →value Snapdragon X Elite PC chip expansion as Qualcomm diversifies from smartphone dependency into the Windows on ARM PC market
- →want automotive AI semiconductor exposure with Snapdragon Digital Chassis design wins representing a multi-year automotive revenue ramp
- →are comfortable with Apple modem dependency reduction, MediaTek competition in premium Android, and limited exposure to the data center AI GPU boom
- →prefer maximum concentration in the AI training GPU market with CUDA software ecosystem lock-in and 80%+ data center AI accelerator share
- →value Nvidia's extraordinary revenue growth trajectory — data center GPU revenue growing 100%+ annually on a $160B+ annualized run rate
- →want the highest-leverage pure-play AI infrastructure investment available in large-cap semiconductors
- →are comfortable with extreme valuation, China export control headwinds, and hyperscaler custom chip competition gradually displacing Nvidia in some AI inference workloads
| Metric | QCOM | NVDA |
|---|---|---|
| AI score | 48.3 | 86.0 |
| AI rank | #562 | #2 |
| Latest close | $226.11 | $210.69 |
| 1M return | +15.59% | -4.50% |
| 6M return | +31.20% | +23.25% |
| 1Y return | +46.39% | +46.19% |
How much would $10,000 be worth today if invested at the start of each period, with all dividends reinvested?
| Period | QCOM | NVDA |
|---|---|---|
| 1Y ago | $14.72K (+47.2%) started 2025-06-18 | $14.48K (+44.8%) started 2025-06-18 |
| 5Y ago | $19.91K (+99.1%) started 2021-06-21 | $114.8K (+1048.0%) started 2021-06-21 |
| 10Y ago | $70.75K (+607.5%) started 2016-06-20 | $1.84M (+18277.9%) started 2016-06-20 |
Hypothetical — past performance does not guarantee future results.
| Metric | QCOM | NVDA |
|---|---|---|
| Market cap | $223.15B | $4.97T |
| Trailing P/E | 22.79 | 31.42 |
| Forward P/E | 19.85 | 16.12 |
| Price/Sales | 3.88 | 23.66 |
| EV/Revenue | 5.14 | 19.43 |
| Analyst target | $180.48 | $298.93 |
| Target upside | -14.75% | +45.69% |
| Metric | QCOM | NVDA |
|---|---|---|
| Revenue growth | -3.50% | 85.20% |
| Earnings growth | 173.00% | 214.50% |
| EPS growth | +173.00% | +214.50% |
| FCF margin | +21.56% | +18.28% |
| Operating margin | 22.06% | 65.60% |
| Profit margin | 22.31% | 62.97% |
| ROIC proxy | 36.08% | 114.29% |
| Return on equity | 36.08% | 114.29% |
| Dividend yield | 1.74% | 0.49% |
| Beta | 1.60 | 2.20 |
| Debt/equity | 55.98 | 6.55 |
| Current ratio | 2.37 | 3.44 |
| Quick ratio | 1.45 | 2.14 |
Lower drawdown and smaller single-period drops generally indicate a smoother ride, though they do not guarantee lower future risk.
| Period | Metric | QCOM | NVDA |
|---|---|---|---|
| 1Y | Growth | +47.18% | +44.82% |
| CAGR | +47.26% | +44.90% | |
| Sharpe ratio | 0.94 | 1.10 | |
| Max drawdown | 33.89% | 20.22% | |
| Max daily drop | 11.46% | 6.20% | |
| Max wkly drop | 23.52% | 10.72% | |
| 5Y | Growth | +83.05% | +1045.71% |
| CAGR | +12.87% | +62.98% | |
| Sharpe ratio | 0.39 | 1.12 | |
| Max drawdown | 44.50% | 66.34% | |
| Max daily drop | 11.46% | 16.97% | |
| Max wkly drop | 23.52% | 22.20% | |
| 10Y | Growth | +436.64% | +17945.12% |
| CAGR | +18.31% | +68.18% | |
| Sharpe ratio | 0.51 | 1.20 | |
| Max drawdown | 44.50% | 66.34% | |
| Max daily drop | 14.95% | 18.76% | |
| Max wkly drop | 23.52% | 28.36% |
| Category | QCOM | NVDA |
|---|---|---|
| Company | Qualcomm Incorporated | NVIDIA Corporation |
| Sector | Technology | Technology |
| Industry | Semiconductors | Semiconductors |
| Core business | Qualcomm is the world's leading mobile semiconductor company, designing Snapdragon processors used in Android smartphones (Samsung, Xiaomi, OnePlus, Google Pixel) and increasingly PCs (Snapdragon X Elite). Qualcomm also generates substantial licensing revenue from its foundational cellular technology patents — any company manufacturing 5G devices pays Qualcomm royalties. Qualcomm's Snapdragon AI features (NPU neural processing units) enable on-device AI inference in phones and PCs without cloud connectivity. | Nvidia designs the world's dominant AI accelerator GPU chips (H100, B200, B300) for data center AI training and inference. Nvidia's CUDA software platform with 4M+ developers creates software lock-in making Nvidia GPUs the default AI computing platform. Nvidia's data center GPU business generates $40B+ quarterly revenue growing rapidly. While Nvidia also has a mobile/edge AI presence (Jetson modules), its primary market is data center AI infrastructure. |
| Investor focus | Investors track handset chip revenue growth, Snapdragon X Elite PC chip adoption (diversifying from smartphones), automotive chip design wins (the next major growth market), and licensing revenue stability. | Investors track data center revenue, Blackwell GPU generation adoption, CUDA ecosystem developer count, and next-generation GPU (Rubin) timeline. |
- →Cellular patent licensing creates $9B+ annual royalty income regardless of which chip company wins — every 5G device manufacturer pays Qualcomm, creating a toll-road royalty business distinct from chip competition
- →Snapdragon X Elite PC chip competes with Apple M-series on performance per watt — Qualcomm's ARM-based PC CPU is driving Windows on ARM adoption
- →Automotive semiconductor design wins (Snapdragon Digital Chassis) represent a multi-year revenue ramp as connected vehicle compute requirements increase
- →80%+ data center AI accelerator market share with CUDA software moat — Nvidia owns the market for AI training GPUs
- →Blackwell B200/B300 GPU architecture delivers generational performance improvements enabling continued AI model scaling
- →Full-stack AI infrastructure from GPU chips through networking (InfiniBand) and software (CUDA/TensorRT) creates a platform competitors cannot fully replicate
- →Apple designs its own modems (reducing Qualcomm modem dependency) and Apple Silicon SoCs — the highest-value smartphone customer is gradually reducing Qualcomm revenue per device
- →Nvidia's AI GPU data center dominance is a different market than Qualcomm's mobile focus — Qualcomm cannot compete in the $40B+ AI training GPU market
- →Samsung and MediaTek develop competing smartphone SoCs — Qualcomm's premium Android market share faces ongoing competition
- →Nvidia's mobile/edge AI chips are outcompeted by Qualcomm's Snapdragon in smartphones and ARM in power-efficient edge devices
- →Custom hyperscaler chips (Google TPU, Amazon Trainium, Meta MTIA) may reduce Nvidia's data center TAM over time
- →Export controls limit AI GPU sales to China
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