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U.S.-listed market research with live data and structured thesis notes.

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Silicon Stack Data Center Fabric AI Software Power + Grid Robotics
ANET AI Data Center Fabric

Arista Networks

AI data-center networking

Detail page

Large AI clusters need fast, reliable, scale-out networking, and Arista is a leader there.

Price $199.53
1D change +2.44%
Market cap $251.65B
Sector Technology
MRVL AI Data Center Fabric

Marvell Technology

Custom AI silicon + optical interconnect

Detail page

Marvell sits in several AI choke points at once: custom accelerators, optical DSPs, interconnect, and scale-up silicon.

Price $240.76
1D change +3.61%
Market cap $216.37B
Sector Technology
ALAB AI Data Center Fabric

Astera Labs

Rack-scale AI connectivity

Detail page

Astera helps solve rack-scale bottlenecks around PCIe, CXL, fabric connectivity, and memory movement.

Price $293.56
1D change +6.59%
Market cap $50.93B
Sector Technology
APH AI Data Center Fabric

Amphenol

High-speed connectors and cabling

Detail page

AI clusters require dense high-speed interconnect, connectors, and copper cabling.

Price $78.37
1D change -0.50%
Market cap $193.26B
Sector Technology

Shared metric table

Live market metrics plus reported quarterly revenue and profit QoQ rows.

Green and red only apply where direction is meaningful. Quarterly revenue and profit cells inherit the sign of the reported QoQ change, which can swing sharply when the prior quarter included a one-time item.

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Metric ANET MRVL ALAB APH
Price $199.53 $240.76 $293.56 $78.37
1D Change +2.44% +3.61% +6.59% -0.50%
Market Cap $251.65B $216.37B $50.93B $193.26B
Enterprise Value $238.31B $212.48B $49.72B $206.78B
Trailing P/E 63.1 76.4 145.3 38.6
Forward P/E 38.7 35.6 45.9 23.9
PEG Ratio 1.48x 1.22x — 0.87x
Price / Sales 23.9 22.9 42.4 6.7
EV / Revenue 22.6 22.5 41.4 7.1
Revenue Growth 37.7% 36.5% 104.5% 55.0%
Earnings Growth 35.7% 50.0% 186.2% 59.3%
Gross Margin 63.0% 52.2% 75.1% 39.0%
Operating Margin 45.4% 16.7% 22.7% 29.8%
Net Margin 38.4% 27.9% 30.7% 17.7%
ROE 31.5% 16.5% 25.8% 38.1%
Free Cash Flow $3.89B $2.41B $91.9M $3.82B
FCF Margin 36.9% 25.5% 7.6% 13.2%
Debt / Equity — 0.29x 2.57x 1.20x
Current Ratio 2.96x 3.17x 0.10x 1.89x
Dividend Yield 0.00% 0.10% 0.00% 0.64%
Next Earnings Nov 03, 2026 Dec 01, 2026 Nov 03, 2026 Oct 28, 2026
Quarterly Revenue $3.04B $2.74B $392.4M $nan
Revenue QoQ +12.1% +13.3% +27.3% nan%
Quarterly Net Income $1.21B $308.0M $153.1M $nan
Net Income QoQ +18.6% +792.8% +90.6% nan%

ANET thesis lens

AI data-center networking

Why it could benefit

  • Large AI clusters need fast, reliable, scale-out networking, and Arista is a leader there.
  • Ethernet's role in AI data centers keeps growing as architectures evolve.
  • Arista is leveraged to both hyperscaler and enterprise data-center modernization.

Moat / edge

  • Strong software layer and operational simplicity.
  • Trusted relationships with sophisticated cloud customers.
  • High-performance Ethernet expertise.

What to watch

  • AI-cluster networking mix versus traditional cloud networking.
  • Customer concentration and spending cadence.
  • Competition from incumbents and custom architectures.

Key risks

  • Large orders can be lumpy quarter to quarter.
  • If architecture choices shift, product mix could change quickly.

MRVL thesis lens

Custom AI silicon + optical interconnect

Why it could benefit

  • Marvell sits in several AI choke points at once: custom accelerators, optical DSPs, interconnect, and scale-up silicon.
  • Hyperscalers building custom AI systems need merchant partners that can help on both compute-adjacent silicon and connectivity.
  • That gives Marvell exposure to the parts of the AI factory that keep getting more complex as clusters scale.

Moat / edge

  • Deep hyperscaler and OEM relationships in complex infrastructure silicon.
  • A differentiated portfolio spanning custom silicon, networking, and optical components.
  • Engineering credibility in performance-sensitive infrastructure markets.

What to watch

  • Custom AI program ramps and customer concentration.
  • Optical interconnect demand versus electrical alternatives.
  • Gross-margin durability as AI mix grows.

Key risks

  • Large design wins can be lumpy and take time to ramp.
  • Execution matters when the thesis depends on several advanced product categories at once.

ALAB thesis lens

Rack-scale AI connectivity

Why it could benefit

  • Astera helps solve rack-scale bottlenecks around PCIe, CXL, fabric connectivity, and memory movement.
  • As AI systems move from single boxes to tightly linked racks, connectivity and orchestration become more valuable.
  • It is one of the cleanest public ways to own the plumbing inside modern AI servers and racks.

Moat / edge

  • Focused product portfolio aimed at specific AI system bottlenecks.
  • Strong alignment with next-generation rack and accelerator architectures.
  • Technical positioning in a market where performance and validation matter a lot.

What to watch

  • Design-win conversion into production revenue.
  • Customer concentration and platform transitions.
  • Adoption of CXL and other rack-scale standards.

Key risks

  • A younger company can see sharper swings as programs ramp.
  • If key customer platforms slip, near-term growth can look worse quickly.

APH thesis lens

High-speed connectors and cabling

Why it could benefit

  • AI clusters require dense high-speed interconnect, connectors, and copper cabling.
  • Amphenol is a broad supplier into data center, communications, auto, and industrial markets.
  • Rack-scale AI designs can raise content per server and per networking platform.

Moat / edge

  • Broad connector and sensor portfolio.
  • Deep customer relationships across high-reliability markets.
  • Scale and acquisition discipline.

What to watch

  • AI data-center organic growth.
  • Margins after acquisitions.
  • Telecom, industrial, and auto cycle recovery.

Key risks

  • A diversified portfolio can dilute pure AI exposure.
  • Connector demand can be cyclical.