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OpenAI, NVIDIA and Anthropic are splitting: how to spend $20, $60 or $200

Three AI strategies are emerging; the practical answer is to keep memory, files, and instructions portable.

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Nate B Jones reads OpenAI’s inference-chip news, the Cursor dispute, and NVIDIA’s response as evidence of three different AI strategies. OpenAI is integrating more of its stack; NVIDIA aims to remain the adaptable supplier for the entire ecosystem; Anthropic is keeping options by diversifying compute sources.

Three different bets

Habanero/Jalapeño is framed as a way to optimize repeated inference workloads. It does not replace NVIDIA systems used for training: OpenAI remains a major NVIDIA customer while seeking better economics and control for specific tasks. NVIDIA is betting on the breadth of its systems, from training to data-center interconnect. Anthropic is pursuing multi-supplier capacity so it can shift work as price and availability change.

Product-dependency risk

The announced withdrawal of future OpenAI models from Cursor makes the user-facing issue tangible. A change in ownership or competitive posture can change model access inside the tool where projects, history, rules, and memory have accumulated. These are loose camps rather than formal alliances, but access uncertainty is real.

A practical buying strategy

At roughly $20 per month, the recommendation is one primary provider that fits weekly work, plus a serious free rival used often enough to remain familiar. At $60, combine two direct subscriptions and, for daily coders, a multi-model coding tool. Above $200, each plan should earn its place through time saved, revenue, cost reduction, or greater output.

The cross-cutting rule is to keep durable assets outside any one platform: files in controlled formats, code in repositories you own, and portable memory or instructions. Switching models will not be seamless, but it becomes far less costly.

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