Anthropic and Samsung explore custom AI chip to reduce Nvidia reliance

If Anthropic proceeds with a Samsung‑designed custom chip, it would mark another major lab trying to vertically integrate its compute stack in response to Nvidia scarcity and pricing power. ([easternherald.com](https://easternherald.com/2026/07/03/anthropic-samsung-custom-ai-chip-talks/)) Google has TPUs, Amazon has Trainium and Inferentia, OpenAI is working with Broadcom, and now Anthropic is testing whether a Korean foundry partner can de‑risk its dependence on cloud‑provided GPUs and TPUs. Custom silicon is expensive, slow and risky—but at current GPU prices, it can be rational for labs committing tens of billions to training.

Strategically, a successful Anthropic–Samsung chip could give Claude’s ecosystem more predictable capacity and potentially lower per‑token costs, allowing Anthropic to be more aggressive on pricing and agentic workloads. It would also deepen the entanglement between US frontier labs and Asian fabs just as Washington and Beijing are escalating chip controls, making the supply chain politics of AI even more complex.

For the race to AGI, more bespoke hardware tuned to large‑scale sequence modelling and tool use likely accelerates progress. When labs can co‑design model architectures and chips, they can push beyond general‑purpose GPU constraints toward higher throughput, better memory bandwidth and lower latency for multi‑modal and agentic systems.