The electricity bill behind AI keeps growing
AMD and Anthropic announced a strategic partnership to deploy up to 2 gigawatts of Instinct MI450 Series GPUs, with the first gigawatt planned for the first half of 2027. AMD also committed to a strategic equity investment of up to $5 billion in Anthropic. This issue covers the July 24 agenda and was published on July 25, 2026 to complete the archive.
A capacity deal and an investment in one package
AMD announced a partnership with Anthropic to deploy up to 2 gigawatts of Instinct MI450 Series GPUs in AMD Helios rack-scale systems. The first gigawatt of that deployment is expected to begin in the first half of 2027. The second leg of the deal is financial: AMD committed to a strategic equity investment of up to $5 billion in Anthropic. In the announcement, AMD Chair and CEO Lisa Su underlined the deepening of the partnership, while Anthropic co-founder and Chief Compute Officer Tom Brown said access to compute is central to keeping Claude at the frontier.
Hardware, software and a two-way arrangement
The deployment is more than GPUs: Anthropic will run AMD Helios rack systems built around Instinct MI455X processors, together with EPYC "Venice" CPUs, Pensando networking and the ROCm software stack. That builds on the MI355X processors the company already uses.
The interesting part is that the arrangement runs both ways: through a multiyear engineering collaboration, the two companies will use Claude to optimize workloads for AMD hardware and to accelerate ROCm software development. AMD also says it will adopt Claude broadly across its engineering and product development teams. In other words, the model takes part in developing the infrastructure that will run it.
The price of a model is the price of chips and power
Nobody discusses gigawatts in the daily life of a business using AI, yet that is the quiet variable behind the bill. Capacity agreements between model companies determine how much compute will exist in the coming years, at what cost and in whose hands. A model company that is not tied to a single supplier reduces its bottleneck risk and gains negotiating room on price. This can be read as a development that lowers the chance of capacity crunches and sudden price moves on the user side, though with investment made now and capacity arriving in 2027, any relief will be spread over time.
What it means for businesses in Türkiye
A business in Türkiye should not expect to be affected directly by this deal; nobody is buying gigawatts. The indirect effect is concrete, though: the cost and availability of AI services depend on how this capacity race resolves. The practical takeaway is not to lock the AI solution you build to a single model. What is affordable today can get expensive tomorrow, and what is slow today can get fast. If you design your systems so that switching models takes a day, price and capacity swings offer you options instead of hitting you. A second note belongs on the data side: whichever model you move to, where your data is processed and stored stays your responsibility under KVKK.
The UNALSOFT take
Our reading is this: we do not pick models for our clients, we build systems that can change models. Which model an agent runs on shifts over time; what should not shift is where the business rules, the permissions and the measurement live. In our Agentic AI service we keep that layer model-independent, so movements in market price and capacity can be managed without disturbing the business's processes.
Invest in the system, not the model.
Let's look at how ready your AI solution is for a change of model.