Broadcom vs NVIDIA
| Company | 2026 AI revenue | Strategy |
|---|
| NVIDIA | $200B+ | Sell GPUs to all markets, including hyperscalers |
| Broadcom | $20B+ | Design custom AI chips for hyperscalers (Google, Meta, Microsoft) |
| Marvell | $5B+ | Custom chips for AWS Trainium, custom networking |
| AMD | $10B+ | Sell GPUs (MI300, MI325, MI355) as NVIDIA alternative |
Source: company earnings, Gartner (2026).
Why custom silicon is winning for hyperscalers
- Cost: Custom chips can be 30-50% cheaper than NVIDIA GPUs for equivalent AI workloads.
- Performance optimization: Custom chips are optimized for specific AI workloads (training vs inference, specific model architectures).
- Supply diversification: Hyperscalers want to reduce dependence on NVIDIA for supply risk.
- Power efficiency: Custom chips can be more power-efficient than GPUs for specific workloads.
- Vertical integration: Hyperscalers want to own their AI hardware stack for differentiation.
Broadcom's networking chip business
Broadcom's networking chip business is a critical enabler of AI data centers. Broadcom designs: (1) Tomahawk 6 — 102.4Tbps Ethernet switches for AI data center fabrics, (2) Tomahawk 5 — 51.2Tbps switches, (3) Jericho 3 — deep-buffer switches for large AI clusters, (4) Silicon Photonics — optical interconnect for high-bandwidth AI networks, (5) NICs — 400G and 800G Ethernet adapters for AI servers. Broadcom networking chips are used in nearly every major AI data center (Broadcom, 2026).
Broadcom's stock and valuation
Broadcom (AVGO) is one of the best-performing AI stocks in 2026: (1) Stock price up 70%+ YTD, (2) Market cap $1.2T+ (now a top 10 US company), (3) Forward P/E ~40x (premium due to AI growth), (4) Stock split 10-for-1 in 2024, (5) Dividend yield ~1.2%. Investors see Broadcom as a less expensive way to invest in the AI custom silicon trend than NVIDIA (Bloomberg, 2026).
What this means for the AI industry
Broadcom's surging AI revenue signals: (1) Custom silicon is a major trend in AI, (2) Hyperscalers want to reduce dependence on NVIDIA, (3) Broadcom is the largest beneficiary of the custom silicon trend, (4) NVIDIA will face increasing competition from custom chips in the hyperscaler segment, (5) The AI chip market is large enough to support multiple winners, not just NVIDIA. Broadcom's success is a positive signal for the broader AI infrastructure buildout (Broadcom, 2026).
Other custom AI chip makers
- Marvell Technology: Custom chips for AWS Trainium, networking chips for AI data centers.
- Alchip Technologies: Custom chips for Asian hyperscalers (Alibaba, Tencent, Baidu).
- GlobalUnichip: TSMC partner for custom AI chip design.
- Tenstorrent (Jim Keller): Open-source RISC-V AI accelerator.
- Cerebras Systems: Wafer-scale AI accelerator for training.
- SambaNova Systems: Reconfigurable dataflow AI accelerator.
- Groq: LPU (Language Processing Unit) for inference.
- Etched.ai: Transformer-specific ASIC.
Resources and next steps
Follow Broadcom investor relations at investors.broadcom.com. For AI chip industry analysis, follow Gartner, IDC, and Forrester. The next Broadcom earnings are expected December 2026. For AI infrastructure investment trends, follow Bank of America, Goldman Sachs, and Morgan Stanley. For Broadcom customer news, follow Google, Meta, and Microsoft quarterly earnings.
Photo: Poeggi, CC BY, via Wikimedia Commons (https://upload.wikimedia.org/wikipedia/commons/3/36/NVIDIA_T20_and_T30_chips.jpg?utm_source=commons.wikimedia.org&utm_campaign=imageinfo&utm_content=original)
Fazlur Rahman
