In-depth analysis of Apple’s memory crisis in 2026: Will Samsung make more money than NVIDIA from selling DRAM?

Core conclusion

In May 2026, memory (DRAM) prices continued to surge, soaring from 15% of the device BOM (material cost) to nearly 40%. Samsung Electronics' profits from selling DRAM memory have exceeded NVIDIA's profits from selling processors, which is called the "Great Memory Panic of 2026." However, with its scale advantages, long-term contracts and vertical integration capabilities, Apple is the most likely player to "get stronger and stronger" in this round of price increases.

Key Points

• Event time: May 2026 (panic began to ferment in January 2026) -Affected objects: All consumer electronics manufacturers, especially the iPhone/Android camp
• Root cause: The memory supply side cannot match the unexpected demand driven by AI
• Apple's response strategy: lock in production capacity with scale + lock in low prices with long-term contracts + capture the market with low-end products (such as $499 iPhone)

Background: Why did memory prices suddenly skyrocket?

Starting in January 2026, the demand for AI-driven device-side inference will explode, causing DRAM and HBM (high-bandwidth memory) demand to far exceed supply. Asymco analyst Horace Dediu calls this phenomenon "The Great Panic of 2026."

Key triggers:

• AI mobile phones and AI PCs require double the memory capacity (from 8GB → 16GB, or even 32GB)
• HBM production capacity is exhausted by AI servers, squeezing ordinary DRAM supply
• Memory manufacturers give priority to supplying high-profit HBM products, and consumer-grade DRAM production capacity is insufficient

The most shocking data: Samsung Electronics' profits from its memory business have exceeded NVIDIA's processor profits - a year ago everyone was still talking about "computing power is king", but now "memory is the new gold."

Key Impact (by Dimension)

Apple’s special advantage: Why is it not afraid of price increases?

Asymco’s analysis reveals Apple’s four layers of defense against rising memory prices:

1. Scale lock: Apple purchases hundreds of millions of DRAM chips every year and signs long-term framework contracts with suppliers (locked in 2-3 years in advance). The soaring prices in the spot market only affect the "marginal purchase volume" and do not affect Apple's base price.

2. Negotiation chips: The semiconductor industry is always cyclical - "There is no semiconductor boom that is not followed by a depression." Apple can use "priority to cooperate with you when the cycle falls" as a bargaining chip to suppress the current price increase.

3. Unified Memory Architecture: Apple Silicon’s Unified Memory Architecture (UMA) is more efficient than the traditional x86 platform - the CPU and GPU share the same memory pool, avoiding the waste of data copies. Coupled with the memory compression and intelligent caching mechanism of macOS, 16GB of unified memory may be equivalent to 24-32GB of x86 platform in actual use experience.

4. Low-end card slot: Apple may be planning a "downward harvesting" strategy - launching the $499 iPhone and MacBook Neo series, using the supply chain cost advantage to cause a dimensionality reduction blow to competitors.

Samsung makes more money than NVIDIA? digital truth

Asymco analysis pointed out that Samsung’s memory business profits in the first quarter of 2026 have exceeded NVIDIA’s processor profits in the same period. This is a landmark event: it means that the "hardware dividend" of the AI ​​boom is shifting from the computing power side to the storage side. For developers, this means:

• In the cost structure of local AI inference, the proportion of memory will continue to increase.
• Devices that choose efficient memory architectures (such as Apple UMA) are more cost-effective in the long term
• The deployment cost of AI Agent/local model will rely more on memory optimization rather than computing power optimization

Adaptation suggestions for AI developers

The rising memory price trend has a direct and far-reaching impact on AI content automation, local model deployment, and AI Agent development.

Task List

• Prioritize Apple Silicon for local AI inference tasks (unified memory architecture advantage)
• Use lighter models in AI Agent workflow to control BOM memory consumption
• Consider a hybrid architecture of cloud inference + local caching to reduce costs
• Pay attention to the developer friendliness of Apple's $499 low-end product line

Reference sources

• Asymco: The great memory panic of 2026
• HN ：How can Apple deal with the memory shortage?
• MacBook Neo Deep Dive: Benchmarks, Wafer Economics

Tool entry

The tool names appearing in the text comply with the platform tool keyword matching rules, and the platform side will automatically process tool_mentions and hover-card: Apple Silicon, macOS, AI Agent, Samsung, NVIDIA

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