Following the July 23 event in San Francisco, AMD received a Buy rating reaffirmation from Goldman Sachs, setting a 12-month target price of $640. The key reasons behind this are the company's partnerships with Anthropic and Microsoft, as well as the forecast of a $2 trillion total addressable market in 2030, reinforcing its growth narrative in AI infrastructure.

This is not just a GPU parameter release. AMD is attempting to shift the AI competition from a single chip to a delivery model encompassing "full rack systems + CPU + network + DPU + software tools + large customer deployments." For investors, the critical question has transitioned from "Does AMD have a stronger GPU?" to "Can it secure large enough AI cluster orders and deliver them on time?"

The target price provided in the report is $640, based on a 32x P/E ratio and estimated normalized earnings per share of $20. With the current stock price at approximately $539.69, the potential upside is around 18.6%; the company has a market capitalization of around $89.05 billion.

Anthropic Places 2GW Order, Microsoft to Receive Helios from H2 2026

The most direct order signal comes from Anthropic.

AMD has entered into a strategic partnership with Anthropic, where Anthropic will deploy a total of 2GW of Instinct M1450 GPUs in the Helios rack-level AI system. The initial 1GW deployment is expected to start in the first half of 2027. AMD also plans to provide Anthropic with up to $5 billion in strategic equity investment. Both parties will collaborate to optimize the Claude model's performance on AMD GPUs and accelerate ROCm software development.

The significance of this type of collaboration goes beyond chip sales. For AI chip suppliers, the deployment by top model companies determines ecosystem credibility. If Anthropic continues to migrate or expand the Claude workload to the AMD platform, it will help AMD demonstrate that its GPU, rack system, and software stack can handle large-scale training and inference requirements.

Microsoft is providing another on-ramp. After expanding their Azure partnership, Microsoft plans to start receiving Helios racks, Venice CPUs, network equipment, and software in the second half of 2026 for cutting-edge model inference, Microsoft's own AI services, and customer applications. Microsoft will also launch two new virtual machines based on the next-generation 2nm Venice CPU and expand the deployment of Pensando DPU in network services.

This means AMD aims to sell GPU, CPU, DPU, and network equipment simultaneously in the cloud provider scenario, rather than just appearing as an accelerator card supplier. For Azure, if the AMD platform can provide sufficient performance and supply elasticity, it will also help reduce single-supply-chain pressure.

A $20 Trillion TAM, Enabled by "Compute Amplification" from Agentive AI

The most impactful number in the report is AMD's upward revision of the total addressable market (TAM) to $20 trillion by 2030.

Specifically, the Data Center AI Accelerator TAM has been raised from $200 billion to $14 trillion, corresponding to a 40% compound annual growth rate; the Server CPU TAM has been raised from $26 billion to $220 billion, corresponding to a 50% compound annual growth rate. AMD also anticipates that by 2030, the company will hold a 50% share of the data center CPU market.

This assumption is based on agentive AI. Compared to single-question-answer tasks, agentive AI needs to call tools, plan tasks, read context, execute multi-step workflows, and handle more inference and orchestration requests. The computational demand is not only on GPUs; CPUs also need to bear scheduling, data preprocessing, system services, and multi-agent workflow orchestration.

This is also the new story AMD wants to tell: AI infrastructure expansion not only boosts accelerator demand but also drives server CPU, network, and system-level solution demand. If the company can package EPYC CPUs, Instinct GPUs, Pensando DPUs, and network equipment into Helios racks, the revenue opportunity will be larger than single-chip sales.

However, this $2 trillion is not the realized market size, but rather a projection based on the widespread adoption of AI-as-a-service by the 2030s. It requires enterprises and cloud providers to continue expanding AI inference deployment and demands that AI applications truly move from pilot to high-frequency production workloads.

Helios Enters Mass Production, AMD to Demonstrate Rack-Level Delivery Capability

At the product level, Helios is the core carrier of AMD's activities this time.

The next-generation Helios AI rack platform is based on the CDNA 5 architecture, with a single GPU achieving a peak performance of 40 PFLOPS (FP4) and 20 PFLOPS (FP8), equipped with 432GB of HBM4 memory and 23.3TB/s memory bandwidth. Each rack integrates 75 GPUs connected via UALink over Ethernet, along with a 96-core EPYC CPU, Salina DPU, and Volcano 800G AI NIC.

The focus of these parameters is not on single-point performance, but on AMD's advancement of the product form towards the entire rack. AI clusters are increasingly relying on system-level design: interconnectivity between GPUs, memory bandwidth, network throughput, CPU scheduling capabilities, and software stack will all affect the final training and inference efficiency.

Helios has entered full production, with shipments scheduled to begin at the end of the third quarter and large-scale production expected in the fourth quarter. Microsoft will receive Helios starting from the second half of 2026, and Anthropic's first 1GW deployment will begin in the first half of 2027, indicating that true large-scale customer validation is still ahead.

AMD has also partnered with Cerebras to combine the Helios system with the Cerebras wafer-scale engine to create a high-performance AI inference solution. The goal is to achieve lower latency, higher energy efficiency, and up to a 5x increase in tokens per watt. This solution is expected to be launched through Cerebras Cloud in the second half of 2026.

On the software side, the ROCm.ai platform has been officially launched, integrating AI tools such as Cursor, Claude, Codex, and Gemini to provide developers with an AI-driven software development experience. The accompanying Hyperloom optimization layer has optimized over 14,000 models, delivering an average performance improvement of 3.3x compared to ROCm 7.

However, the ROCm.ai and Cerebras partnership is more suitable as a complement to the Helios ecosystem rather than the main focus of this article. Ultimately, investors will look to see if customers can reliably use the AMD platform in real-world workloads, rather than just focusing on whether the tools and partnership list are extensive enough.

Valuation Bet Has Risen, Risk Lies in 2026-2027 Delivery

Goldman Sachs Financials forecasts that AMD's revenue in 2026 is estimated to be around $50.57 billion, with an EPS of $6.20; revenue in 2027 is approximately $86.01 billion, with an EPS of $13.20; revenue in 2028 is about $109.0 billion, with an EPS of $17.90.

These projections imply that the market has high expectations for AMD's AI revenue growth, margin improvement, and operating leverage release over the next two to three years. The $640 target price not only reflects the current product releases but also includes the shipment of Helios, Microsoft Azure deployment, the initial deployment of Anthropic 1GW, and improvements in the ROCm ecosystem, among other simultaneous advancements.

The real divergence also lies here.

First, the adoption speed of agent-based AI may be slower than expected. If enterprise AI workflows do not rapidly expand, the assumption of a $20 trillion total computing market in 2030 will be revised downward.

Second, there is still a timing gap in large customer GPU deployments. Microsoft's Helios reception is set to begin in the second half of 2026, with the initial deployment of Anthropic 1GW expected to start in the first half of 2027, and short-term financial reports cannot fully validate the revenue contribution of these partnerships.

Third, competitive pressure will not disappear. NVIDIA still holds a dominant position in AI accelerators and software ecosystems, and whether ROCm can narrow the developer experience gap will impact AMD's ability to be a viable alternative in large-scale customers.

Fourth, the x86 architecture also faces market share risk in the enterprise AI scenario. If more customers adopt custom chips, Arm servers, or other heterogeneous solutions, AMD's expectations for CPU TAM and its 50% data center CPU share will be challenged.

This makes AMD's story more like an execution test: the reports have pushed the market space, customer orders, and target price to higher levels. Whether the stock price can continue to digest these numbers will depend on whether Helios can ship as planned, whether Microsoft and Anthropic can expand deployments as scheduled, and whether AI demand can truly support the $20 trillion market by 2030.

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