Anthropic is establishing an internal chip-design team to develop custom processors for its Claude artificial intelligence models, aiming to mitigate reliance on constrained AI hardware supplies. The move coincides with the company exploring a $36 billion debt financing package tied to Alphabet Inc.’s Google chips, a figure that would surpass a previously agreed $35 billion debt arrangement with Apollo Global Management and Blackstone. This dual strategy of proprietary hardware development and massive capital raising highlights the intensifying competition for compute resources among leading AI firms.

The initiative addresses a critical bottleneck in the AI industry: the scarcity of advanced chips required for training and running frontier models. While Anthropic continues to utilize a multi-chip strategy involving third-party infrastructure from Amazon Web Services, Google, Nvidia, and AMD, the push for custom silicon seeks to optimize performance and efficiency at scale. Developing such cutting-edge AI chips reportedly costs roughly $500 million, reflecting the high expense of recruiting specialized engineers and ensuring scalable manufacturing.

Strategic Shifts and Financing

Anthropic’s expansion into hardware design marks a significant evolution in its relationship with cloud providers and semiconductor manufacturers. The company maintains deep ties with Amazon, which has invested billions in Anthropic and provides access to Trainium and Inferentia chips through AWS. In April, Amazon announced that Anthropic would spend more than $100 billion over the next 10 years on AWS technologies. Despite this commitment, the new chip team signals a desire for greater independence and control over the underlying hardware stack.

The financial scale of Anthropic’s ambitions is underscored by its ongoing negotiations for debt financing. The potential $36 billion package, which Blackstone is reportedly discussing with investors, would support the lease of Google’s custom AI chips. This deal structure aims to secure long-term access to essential compute capacity without relying solely on equity or existing cash reserves. The size, structure, and leadership of this financing remain under negotiation, with no guarantee that Blackstone will lead the transaction.

What the Numbers Show

The juxtaposition of a $500 million per-chip development cost against a $36 billion financing effort illustrates the capital intensity of modern AI infrastructure. The new $36 billion debt target, exceeding the previous $35 billion agreement, suggests an accelerating pace of spending as Anthropic scales its operations. This increase in leverage indicates that the company views access to specialized compute—whether through custom designs or leased Google chips—as a non-negotiable priority for maintaining competitiveness against rivals like OpenAI and Google. The lack of a disclosed timeline for custom chip deployment further emphasizes that immediate reliance on third-party accelerators will continue alongside long-term hardware independence efforts.

The European Commission has expanded its authority to oversee the world’s most advanced artificial intelligence systems, giving regulators new powers to scrutinize general-purpose AI models before they are released across the European Union. Under the latest enforcement phase of the EU AI Act, approved in 2024, regulators can demand model evaluations from leading developers and restrict systems deemed to pose significant risks. This expansion directly impacts major AI firms such as Anthropic and OpenAI, increasing compliance costs and operational scrutiny for companies deploying foundation models in Europe.

Companies that violate the new rules could face substantial financial penalties. Fines can reach up to $17 million (€15 million) or 3% of annual global revenue, whichever amount is higher. The oversight regime is part of a phased rollout designed to create stricter guardrails around high-impact AI technologies. Henna Virkkunen, the European Commission’s executive vice president for tech sovereignty, security and democracy, warned that risks from advanced AI models require heightened scrutiny.

"Harms can occur if AI is not properly designed and used and the most advanced models create risks on an entirely new scale," Virkkunen said.

The crackdown adds another point of tension between the U.S. and Europe over technology policy. Washington and Brussels have clashed over Europe’s efforts to reduce reliance on American technology companies and impose penalties on U.S.-based firms. In July, European regulators issued Google a €1 billion penalty under Digital Markets Act rules, prompting President Donald Trump to threaten the EU with a "substantial" tariff.

Regulatory exposure extends beyond where an AI company is headquartered. Elisabetta Righini, a partner at Sidley Austin, noted that U.S. companies cannot avoid EU oversight simply by operating outside the bloc. Non-European AI providers must appoint an EU-based authorized representative to communicate with regulators.

Righini added that companies could face penalties not only for model-related safety failures but also for failing to cooperate with regulators. "What’s rarely appreciated is that GPAI liability isn’t limited to substantive breaches: refusing an information request, giving misleading answers, or blocking a model evaluation is fineable on its own," she said.

OpenAI said it has been working with European regulators as the new framework takes effect. Tom Gordon, OpenAI’s vice president for EMEA policy, stated that the company has "collaborated closely with the European Commission and the wider ecosystem on implementing the AI Act, including its Codes of Practice." Google also said it expects to comply with the new requirements as the rules and related guidance are implemented.