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Jensen Huang Admitted He Was Facing an "Avalanche" of Excess Wafers and Memory

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For the past two years, the narrative around inflated GPU and RAM prices has been the insatiable AI demand eating up wafer at TSMC and every module on Earth must go to AI data centers. However, the narrative is cracking ever since reports of channel stuffing and over commitments came out.

Now with Nvidia’s former CEO Jensen Huang gone, more details are out that corroborate our earlier reports on inflated demand on AI. According to Wall Street Journal, Huang admitted in August that major cloud providers are moving away from Nvidia in favor of in-house chips, leaving Nvidia staring down a massive oversupply of prepaid TSMC silicon and memory that was “coming at him like an ‘avalanche'”.

The WSJ report details a heated clash in August 2026 between Huang and Nvidia’s longtime Chief Financial Officer, Colette Kress, the executive who has now taken over as Nvidia’s interim CEO.

Kress was concerned about Nvidia’s growing financial exposure and wanted to rein in the company’s “circular financing” commitments to cloud providers, and AI companies like OpenAI and Anthropic.

While early talks had floated backstopping roughly 8 gigawatts of OpenAI compute (worth up to $250 billion), Kress successfully scaled Nvidia’s signed guarantee cap down to roughly 4.25 gigawatts, or up to $125 billion.

In an August meeting, Huang belittled Kress for questioning the deals, calling her “a deer in the headlights”. To justify why Nvidia needed to financially backstop OpenAI and smaller cloud providers to keep buying its GPUs, Huang admitted that Nvidia was caught in a massive squeeze.

Then he went on to describe the situation the company was in. Major cloud providers were running away from Nvidia, making plans to use alternative chips and lessen their reliance on the firm. Even worse, Huang said, the vast supply of chip wafers and memory Nvidia had committed to buying were coming at him like an ‘avalanche.’ Per the WSJ

Then he went on to describe the situation the company was in. Major cloud providers were running away from Nvidia, making plans to use alternative chips and lessen their reliance on the firm. Even worse, Huang said, the vast supply of chip wafers and memory Nvidia had committed to buying were coming at him like an ‘avalanche.’

Nvidia has reportedly contacted TSMC to wind down their chip orders.

For PC builders and hardware enthusiast the reported admission is validating, and quite glaring. Jensen Huang, instead of allowing excess TSMC wafer capacity and memory flow back into reasonable priced GeForce products and broader DRAM production, allegedly scrambled to use its own balance sheet to finance data center buildouts so AI startups and absorb Nvidia’s over-ordered chips.

The $500bn deal? Fake. The $100bn OpenAI deal? Fake. Jensen and NVIDIA have built their legacies on deception. They tried to rig 5060 interviews, and threatened @GamersNexus. This company sucks and has sucked for a while and everybody wants to pretend it's a sudden event. https://t.co/cpaIXwfp5d— Ed Zitron (@edzitron) November 12, 2026

The $500bn deal? Fake. The $100bn OpenAI deal? Fake. Jensen and NVIDIA have built their legacies on deception. They tried to rig 5060 interviews, and threatened @GamersNexus. This company sucks and has sucked for a while and everybody wants to pretend it's a sudden event. https://t.co/cpaIXwfp5d

Reports of glut of unsold hardware have been around for a while, but only now mainstream media is catching up to what Nvidia was reportedly doing. Many industry analysts including Ed Zitron reported months ago how Nvidia and other companies have exposed themselves to devastating financial risk, and also made sure to channel stuff META, Google, Amazon, and others by leveraging their FOMO.

Zitron estimated that at least $200 billion worth of Nvidia AI chips are sitting idle in warehouses, purchased by cloud giants that lacked the electrical grid capacity or immediate end-user demand to plug them in.

The bottom line is, AI demand is no way near as high that it would consume this much silicon.

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