According to a report from The Information, Apple is accelerating its merger and acquisition strategy to bolster its AI server chip capabilities. The company has been actively seeking acquisition targets over the past few months, engaging with investment banks and several semiconductor startups to evaluate potential deals.

This move comes as the company's in-house development of its next-generation AI server chip, codenamed Baltra, has reportedly been delayed. Meanwhile, its current M2 Ultra chip is said to be reaching performance limits for data center AI tasks, forcing Apple to offload some of these heavy workloads to NVIDIA infrastructure hosted on Google Cloud.

M2 Ultra Performance Limits and Baltra Delay

Currently, Apple's AI data center compute relies on the M2 Ultra chip. However, as the scale of AI workloads expands, the internal servers are reportedly hitting performance bottlenecks. The Information's report states that the next-generation Baltra chip, originally planned for release this year, has been postponed. Until Baltra is ready, Apple is outsourcing some intensive AI tasks to external infrastructure, which currently runs on NVIDIA chips via Google Cloud. This situation creates a dual dependency on external suppliers for Apple's core AI infrastructure at a time when AI models are rapidly evolving.

It is noteworthy that a Morgan Stanley report previously disclosed that Apple is securing a large portion of TSMC's SoIC advanced packaging capacity for Baltra, with orders for 36,000 wafers in 2026 and a surge to 60,000 wafers projected for 2027.

Acquisition Strategy and Potential Targets

Apple's acquisition of the Israeli AI startup Q.ai for nearly $2 billion in January marked a significant shift in its M&A approach, representing its second-largest deal ever. Q.ai specializes in technology that interprets speech through facial micro-movements. This acquisition demonstrated a path for Apple to quickly fill capability gaps when internal development lags, a strategy now seemingly being applied to the AI server chip domain.

The report, citing sources familiar with the matter, indicates that Apple recently held talks with the startup PrismML, which focuses on model compression technology. PrismML claims its technology can compress a 27-billion-parameter large language model to run locally on an iPhone without performance loss, a key capability for Apple's vision of on-device AI.

At this stage, Apple has not publicly disclosed any specific acquisition targets or the potential scale of any deals. These discussions are reportedly still in early evaluation phases. It is important to note that the competitive landscape for AI server chips is highly concentrated, with NVIDIA holding a dominant position. For Apple to meaningfully enhance its AI compute power through acquisition, any target would need to meet high thresholds for both technological maturity and strategic fit.