NVIDIA Market Analysis: Why Stock Isn't Reacting to Custom Chip Competition

This analysis is based on a Reddit discussion [0] published on November 6, 2025, questioning why NVIDIA stock isn’t reacting to scaled custom chip deployments from Google and Amazon, followed by comprehensive market analysis of this competitive dynamic.

NVIDIA stock is currently trading at $188.08, down 3.65% on the day, with a modest +1.37% gain over the past 30 days [0]. This relative resilience occurs despite significant competitive developments in the custom AI accelerator space. The company’s data center revenue reached $115.19 billion in FY2025, representing 88.3% of total revenue [0], indicating continued dominance in AI infrastructure spending.

Google has deployed seventh-generation Ironwood TPUs with performance specifications that directly challenge NVIDIA’s Blackwell GPUs. Each Ironwood TPU delivers 4.6 petaFLOPS of FP8 performance, slightly exceeding NVIDIA’s B200 at 4.5 petaFLOPS [1]. The TPUs feature 192GB of HBM3e memory with 7.4 TB/s bandwidth, making them competitive on technical specifications. Google’s key advantage lies in massive scalability, offering TPU pods up to 9,216 chips with potential for 400,000+ accelerators in a single cluster [1].

The more immediate competitive pressure comes from Amazon’s Trainium2 deployment. Anthropic is currently running on 500,000 of Amazon’s custom Trainium2 chips, with plans to scale to over 1 million by year-end [2]. AWS claims Trainium2 delivers 30-40% better price-performance than GPU-based instances for training workloads, which could translate to hundreds of millions in savings for AI companies spending billions annually on compute [2]. Amazon’s $8 billion investment in Anthropic creates a circular ecosystem that could accelerate custom chip adoption [2].

Despite these competitive threats, 73.4% of analysts maintain “Buy” ratings on NVIDIA with a consensus price target of $235.00, representing 24.9% upside from current levels [0]. Recent analyst actions from major firms including Goldman Sachs, B of A Securities, and UBS all maintain “Buy” ratings [0].

However, valuation concerns are evident with NVIDIA trading at elevated multiples (P/E: 52.92x, EV/OCF: 59.43x) [0]. The stock’s remarkable 3-year performance of +1,215.24% suggests that high expectations may already be priced into the current valuation.

Amazon is executing a dual strategy - serving both OpenAI with NVIDIA GPUs and Anthropic with custom Trainium2 chips [2]. This approach means NVIDIA continues to benefit from massive infrastructure deals even as alternatives emerge. The market appears to recognize that custom chip development doesn’t necessarily mean immediate NVIDIA revenue displacement.

Analysts project NVIDIA’s market share declining from 95% in 2024 to 60% by 2027 [2]. This represents a gradual transition rather than immediate disruption, giving the market time to adjust expectations. The timeline allows NVIDIA to continue generating substantial revenue even as competitive pressures increase.

NVIDIA’s CUDA software ecosystem continues to provide significant competitive advantages. While frameworks like PyTorch 2.0 and OpenAI’s Triton compiler are gradually reducing switching costs [2], the entrenched nature of CUDA in production AI workloads creates a substantial barrier to rapid migration.

Microsoft and Amazon represent 39% of NVIDIA’s revenue [2], and their accelerated custom chip development poses significant structural risk. However, the market appears to be pricing this as a known factor rather than a surprise development.

The primary risk is that the transition to custom chips could accelerate faster than the projected timeline. If cost advantages of 40-50% for custom chips [2] prove compelling across broader use cases, NVIDIA’s market share decline could be steeper than anticipated.

As NVIDIA transitions from “irreplaceable monopoly” to “leading semiconductor company with normalizing margins,” valuation multiples could compress from 50x earnings to 25-30x [2]. This compression could occur even if revenue remains strong, as the growth premium diminishes.

Amazon’s investment in Anthropic and similar arrangements could mask weaker organic demand for NVIDIA GPUs [2]. If circular deals represent a significant portion of growth, the underlying market dynamics may be weaker than apparent.

NVIDIA maintains opportunities to extend its lead through next-generation hardware and software integration. The company’s ability to stay ahead of custom chip developments could preserve premium positioning.

Custom chips primarily serve hyperscalers’ internal workloads, not the broader enterprise market. NVIDIA could capture growing enterprise AI deployment demand that hyperscalers’ custom solutions don’t address.

Continued investment in CUDA and AI software tools could deepen the moat around NVIDIA’s ecosystem, making migration costs prohibitively high for production workloads.

Independent validation of performance claims and cost savings will be crucial [2]. If Trainium2 demonstrates clear advantages at scale, it could accelerate adoption across other customers.

The balance between NVIDIA GPUs and alternative chips in OpenAI’s multi-cloud strategy will indicate how quickly major AI companies are diversifying away from NVIDIA [2].

Tracking how much of AWS’s 20% growth comes from circular deals versus organic enterprise demand will reveal the true health of the AI infrastructure market [2].

The market’s muted reaction to Google’s TPU and Amazon’s Trainium2 deployments reflects a complex assessment of competitive threats versus NVIDIA’s continued strengths. While custom chips represent genuine competitive pressure with significant technical capabilities and cost advantages, several factors explain the measured market response:

1. Gradual Transition Timeline:
   Market share erosion is projected over several years, not immediately
2. Dual Strategy Buffer:
   Major customers like Amazon continue purchasing NVIDIA GPUs while developing alternatives
3. Software Ecosystem Persistence:
   CUDA’s entrenched position creates high switching costs
4. Continued Revenue Growth:
   NVIDIA’s data center business shows strong growth despite competition
5. Analyst Optimism:
   Professional consensus remains bullish with significant price targets

However, the structural shift toward custom silicon represents a significant long-term risk to NVIDIA’s premium valuation. The combination of major customers developing competing alternatives and elevated valuation multiples creates notable downside risk if the transition accelerates faster than expected [2]. Historical patterns suggest that when market leaders lose technological moats while trading at premium multiples, valuation compression can be swift and severe.

Users should be aware that while NVIDIA’s current position appears strong, the competitive landscape is evolving rapidly. The company’s elevated valuation multiples and customer concentration create vulnerability if custom chip adoption accelerates beyond current projections. Market participants should monitor key indicators including independent performance benchmarks, customer adoption rates, and the decomposition of growth between organic demand and circular financing arrangements.