AI computing power dual market linkage: Behind Samsung and SK Hynix's trillion-dollar market value, why do RENDER and FIL rise in sync?

In May 2026, the global capital markets are simultaneously showcasing two seemingly parallel, yet deeply interconnected price trajectories: on one side, South Korea's memory chip giants Samsung Electronics and SK Hynix have consecutively hit record highs, with market values surpassing the trillion-dollar mark; on the other side, decentralized computing power and storage tokens represented by Render Network (RENDER) and Filecoin (FIL) have recorded significant gains over the past thirty days.

These two asset groups belong to entirely different market systems—traditional stock markets and crypto asset markets—with fundamentally different valuation frameworks, investor structures, and liquidity logic. Yet, they are being linked by the same main thread: structural shortages in AI computing power.

This is not mere coincidence but a cross-market revaluation of value triggered by supply and demand imbalances in the physical world.

Storage Innovators in the Trillion-Dollar Club

On May 6, 2026, Samsung Electronics' stock price surged intraday by nearly 16%, reaching 270,000 Korean won per share, a new all-time high, closing the day up 14.41%, with its market capitalization breaking through the $1 trillion threshold, making it the second Asian tech company after TSMC to reach this milestone. The rally continued; on May 27, driven by the formal approval of labor agreements, Samsung hit another record high, closing up 2.68% for the day.

Following closely, SK Hynix's stock price on May 27 soared by 11% at one point, officially crossing the $1 trillion market cap mark, becoming the third Asian company to join the trillion-dollar club. Since the start of 2026, SK Hynix's stock has surged approximately 250%. On the same day, the Korea KOSPI index's gains expanded to 5%, triggering a circuit breaker and halting trading for five minutes.

In the U.S. stock market, Micron Technology closed up 19.29% on May 26, with its share price at $895.88, marking its first time surpassing a $1 trillion market value, with its stock price multiplying eightfold over the past year. Thus, within just a few weeks, the three major global memory chip giants—Samsung Electronics, SK Hynix, and Micron—successfully reached the trillion-dollar valuation milestone.

Meanwhile, in the crypto market, according to Gate market data, as of May 28, 2026, RENDER was priced at $2.1023, up 21.68% over the past 30 days; FIL was priced at $1.0414, with a 12.05% increase in the same period. The upward momentum of these two decentralized infrastructure tokens closely overlaps in time with the surge in traditional semiconductor stocks.

From GPU Shortages to a Chain-Wide Computing Power Crisis

The underlying driver of all this is a sector-wide shortage of computing power across the entire AI industry.

From late 2025 into early 2026, as large AI models shift from training to large-scale inference deployment, global demand for computing power has entered an exponential growth phase. IDC forecasts that the number of active AI agents worldwide will grow from 28.6 million in 2025 to 2.216 billion in 2030, an increase of nearly 80 times over five years. Data from China's National Data Bureau shows that by March 2026, China's daily token call volume exceeded 140 trillion, a 1,400-fold increase from early 2024's 100 billion.

While demand explodes, supply faces a structural deadlock.

Goldman Sachs research indicates that in 2026, the global supply-demand gaps for DRAM, NAND flash, and HBM are 4.9%, 4.2%, and 5.1%, respectively—highest since 2011. More critically, according to Feng Li, President of SEMI China, HBM capacity shortages reach 50-60%, with the three major memory manufacturers already prioritizing 70% of new capacity expansion toward HBM and related advanced packaging. SK Hynix's HBM capacity by the end of 2026 has been pre-locked by major AI clients.

The spot market for GPUs is also under pressure. The one-year lease rate for H100 GPUs increased by nearly 40% within six months, from $1.70/hour in October 2025 to $2.35/hour in March 2026; spot prices have surged to approximately $4.08/hour. High-end GPUs like Nvidia's B200 are nearly "invisible" in the domestic market, with H200 spot prices even higher than the new generation B200, creating an inversion.

This shortage is not a traditional cyclical supply-demand fluctuation but a structural capacity squeeze driven by AI application explosions. The core bottleneck of computing power has shifted from "slow calculation" to "slow movement"—GPU performance heavily depends on HBM, whose capacity expansion is limited by complex processes like advanced packaging and through-silicon vias, with large-scale new capacity releases not expected before 2028.

Overlay of Supply-Demand Logic Revealed by Multiple Layers

By aligning the growth in AI computing demand, the stock price movements of Samsung and SK Hynix, and the price changes of RENDER and FIL on the same timeline, a clear "demand transmission chain" emerges.

First Layer: Fundamental Drivers on the Demand Side. In early 2026, tech giants Google, Microsoft, Amazon, and Meta announced combined annual capital expenditures of approximately $725 billion, a significant portion of which flows directly into data center expansion and large model training clusters. A single AI server requires 8 to 10 times more DRAM than traditional servers and three times more NAND Flash. TrendForce data estimates that global capital expenditure by the top nine cloud providers will reach about $830 billion in 2026, with an annual growth rate of 79%.

Second Layer: Value Capture in Semiconductor Manufacturing. Samsung Electronics' Q1 operating profit reached 57.2 trillion won, surpassing the full-year 2025 level, up 756% year-over-year. SK Hynix's Q1 operating profit grew 405% YoY to 37.6 trillion won, with an operating margin of about 72%. The pricing for HBM4 modules is around $700, 20-30% higher than the previous HBM3E generation, with an expected operating margin of 50-60%. The three major memory manufacturers now hold unprecedented bargaining power over the world's largest tech companies, and shortages are expected to persist into 2027.

Third Layer: Spillover Effects in Decentralized Networks. When centralized computing supply cannot meet demand, capital begins seeking alternative paths. Render Network generated $38 million in monthly revenue in January 2026, ranking second among global DePIN projects, operating 5,600 active GPU nodes. In April 2026, through the RNP-023 governance proposal, Render Network integrated about 60,000 GPUs from Salad Network, greatly enhancing its capacity to handle large-scale AI training and rendering tasks. Filecoin's foundation announced a strategic shift in 2026 from "expanding supply" to "expanding paid demand," focusing on AI agents, on-chain data, and real-world assets. The AI infrastructure demand has nearly booked all of 2026's storage capacity, with supply shortages first boosting stocks of traditional hard drive manufacturers, then rotating into their crypto counterparts.

The following table illustrates this complete value transmission path from upstream to downstream:

| Industry Chain Level | Core Bottleneck | Representative Assets | Market Type | | --- | --- | --- | --- | | Silicon wafers and raw materials | Advanced process capacity constraints | Samsung Electronics, SK Hynix | Traditional stock market | | Storage and packaging | HBM capacity gap 50-60% | Micron Technology | Traditional stock market | | GPU and computing hardware | B200 supply tight, delivery delays | Nvidia | Traditional stock market | | Data center hosting | Power and cooling infrastructure shortages | IREN, Cipher Digital | Traditional stock market (mining firms transforming) | | Decentralized computing power | Aggregating idle GPU resources | Render Network | Crypto market | | Decentralized storage | Surge in AI data storage demand | Filecoin | Crypto market |

Structurally, decentralized computing networks are not meant to replace Nvidia or Samsung but to provide incremental supply at the "edge" where existing supply chains cannot reach. The relationship is not substitution but complementarity.

Multiple Consensus and Key Disagreements

Bull Camp's Core Narrative

Optimists believe that this super cycle in storage chips differs fundamentally from previous cyclical booms. UBS describes the current cycle as a "once-in-three-decades" storage super cycle, raising the 2026 HBM terminal bit demand estimate to 32.9 billion Gb, up 88% annually, and further revising 2027 estimates to 58 billion Gb. Nomura Securities offers an optimistic target price of 590,000 won for Samsung Electronics; for SK Hynix, a target of 4 million won.

On the crypto side, bulls argue that GPU shortages create fertile ground for decentralized physical infrastructure networks to explode. When AI startups face severe GPU shortages because cloud providers prioritize internal teams and top clients, platforms like Render Network become the "pricing setters" for the "long tail" of computing power. Filecoin also benefits from rising AI data storage costs, with shifting demand toward decentralized storage accelerating.

Bearish Skepticism

Counterarguments are also noteworthy. On Wall Street, skeptics warn that the cyclical nature of storage chip industries will not disappear because of AI. Samsung and SK Hynix remain cautious about increasing DRAM output, fearing that aggressive expansion could lead to oversupply once AI demand stabilizes. The unprecedented concentration risk in Korea's stock market also rings alarm bells.

In the crypto market, critics point out that some DePIN tokens have fallen 94-99% from their all-time highs, making them among the worst-performing sectors. The core challenge for DePIN projects is not "insufficient computing power" but the fixed issuance models that, during demand downturns, create negative feedback loops of power loss. Despite a 30-day rally, RENDER has still fallen 52.28% over the past year, and FIL has declined 64.03%, indicating that token prices remain affected by the overall volatility of the crypto market.

Industry Impact: Miner Transition and Supply Chain Reshaping

One of the most profound structural impacts of this AI computing power shortage is the large-scale transformation of Bitcoin miners into AI data center operators.

By mid-2026, the industry has signed over $70 billion in contracts related to AI and high-performance computing, with some miners expecting up to 70% of their revenue to come from AI by year's end, effectively transforming into data center operators. Hut 8, for example, uses Bitcoin as collateral to establish a leasing base worth up to $16.8 billion. IREN has procured Nvidia's Blackwell architecture AI systems from Dell for about $1.6 billion to support a five-year, $3.4 billion cloud computing contract.

Compared to cloud giants building from scratch, miner-turned-data-center operators have clear advantages: their infrastructure, power, and sites are already in place, with grid connections, substations, and available parks, ready for quick deployment with minor upgrades, and they can lock in cash flow through multi-year AI contracts.

This trend triggers two chain reactions in the crypto market: on one hand, miners sell large amounts of Bitcoin to fund AI infrastructure, with listed miners having reduced holdings by over 15,000 BTC, exerting some pressure on Bitcoin's network hash rate and market price; on the other hand, their transformation creates a bridge connecting traditional AI computing markets and crypto markets, leading to overlapping valuation logic.

Conclusion

AI computing power is becoming a universal pricing language across asset classes. From Samsung's HBM production lines in Pyeongtaek, to the approximately 60,000 idle GPUs aggregated on Render Network, and the AI training datasets stored on Filecoin, the same demand curve is being priced in different ways.

Traditional stock markets and crypto markets are not two forever parallel lines. When physical supply and demand imbalances reach a significant scale, value flows bidirectionally along the industry chain—initially consolidating as profits and market value in semiconductor manufacturing, then spilling over into token prices via decentralized networks.

This does not mean RENDER or FIL will replicate Samsung and SK Hynix's gains, nor that decentralized computing power can replace Nvidia's GPU clusters. But it reveals an ongoing trend: under the common theme of AI computing power, two originally isolated market systems are building a linkage based on underlying supply and demand logic. Understanding this relationship may be more important than predicting the price trajectory of any single asset.