BN · rank #20 · 2026-07-23
NXPI
NASDAQ · $70.39B (USD)
The exact numbers the algorithm saw.
| Composite score Z-score blend of the factors below; drives the rank. | 0.08 |
|---|---|
| Forward revenue growth Consensus forward revenue growth. | +10.8% |
| Forward net margin Consensus forward net margin. | +22.8% |
| Net margin TTM Trailing twelve month net margin. | +21.0% |
| Margin expansion Forward minus trailing net margin (percentage points). | +1.8% |
| Forward PEG Forward P/E to growth. Below 1 is cheap for the growth. | 0.69 |
| Debt / FCF Net debt relative to free cash flow. Lower is safer. | 3.96× |
| Analyst upside Spread between the consensus 12m target and the current price. | +12.4% |
| Last EPS surprise Most recent reported EPS versus consensus. | +2% |
| Market cap (USD) | $70.39B |
The AI research card
Independent qualitative review of each pick before the order is placed. On the rare day the research service is unavailable, the paper book trades on the quant ranking alone and no card appears here.
Summary
NXP Semiconductors is a leading automotive and industrial edge semiconductor supplier whose domain-specific SoCs, radar chips, and secure AI processors are deeply embedded in multi-year vehicle and industrial design cycles.
Rationale
The bottleneck-solver thesis is reinforced by NXP's single-chip radar SoCs with on-sensor L2/L2+ ADAS processing, S32N7 zonal compute, and eIQ Agentic AI framework — proprietary, hard-to-displace components in software-defined vehicle and physical AI pipelines — supported by a 0.69 forward PEG and 12% analyst upside at a $70B cap.
Material risks
- 1NXP does not own the full AI stack and depends on NVIDIA and GE HealthCare collaborations for advanced AI differentiation — if either partner internalizes edge inference silicon or shifts to a competing supplier, NXP's bottleneck positioning in physical AI erodes materially.
- 2April 2026 distributor-level price increases risk accelerating customer qualification of Texas Instruments or Infineon alternatives in industrial/IoT, where design-in cycles are shorter than automotive and switching costs are lower.
AI verdict council
Each pick is reviewed independently by 3 models before any order. 2 of 3 voted to proceed.