Source: Company Information; Leverage Shares analysis

R&D’s share of operating expenses has grown ever-larger as the company expends vast amounts of capital in delivering AI-compatible solutions across the board. Nonetheless, the company’s operating margin is set to limp back to the 20+% levels that were seen in FY22 and FY23. Meanwhile, net profit margin has already regained the levels seen in these FYs. A lot of this pass-through efficiency between net income and revenue comes from the company steadily raising licensing fees for its IP and royalties for each chip its customers sell.

Despite such success, a rationalization narrative is being imputed on the stock, and a lot of these might be implied from the lessons learned from DeepSeek’s reported performance.

(Chinese: 深度求索) is a Chinese AI software company owned and funded by Chinese hedge fund High-Flyer. The company’s DeepSeek-R1 model essentially shook up the industry recently after ostensibly matching OpenAI-level performance standards despite utilizing the likes of the NVIDIA H800, a chipset that is well behind in terms of complexity when compared to the likes of H100 used by American tech leaders.

In its stated current form, DeepSeek is a highly viable alternative to the costs incurred by most companies looking for entry- to mid-level chatbot applications. Given that it’s a fairly new entrant, third-party support is scarce but the likes of GitHub are rapidly fulling up with solutions that can be added as a „layer“ to will streamline usage.

Now, DeepSeek is repeatedly stated in media sources as being „open-source“. However, this doesn’t mean that anyone can download the training code, i.e. the part of the algorithm that does the computational/logical analysis. Instead, it’s open-weight¹ – which means that it makes the inner workings leading to the arrival at a response/conclusion visible to the end user without making the engine itself visible. Despite that, this is potentially an enormous learning advantage for startups all over the world looking to enter the commercial AI model space: it is entirely conceivable that the gap between OpenAI and, say, India’s Krutrim might have been reduced from (possibly) a decade to a matter of a couple of years. The AI model space is potentially poised to witness explosive growth.

Overall consensus among analysts is that infrastructure buildouts are far in excess of computation requirements. DeepSeek ostensibly asserts that its relatively-par performance, despite lower-capability architecture, was achieved via low-level code optimizations². This has enormous repercussions for the industry: for most clients, DeepSeek’s success implies that „less“ might be enough. In other words, success isn’t bound by a „hardware“ problem but a „coding“ problem.

If so, why should datacenters continue to allocate budgets for the next generation of chipsets when current capacity can be increased simply via „better“ code? Also, what does this mean for the forward outlook of companies dependent on buy-ins of cutting-edge computation infrastructure?

In the course of its earnings release, the company did narrow its revenue guidance to a range of $3.94 billion to $4.04 billion from $3.8 billion to $4.1 billion for the full year. This lent weight to speculations that datacenters already at excess capacity are likely starting to pull back from spending.

There are early signs of a rationalization afoot in tech stocks‘ valuations, which isn’t all too surprising. While the DeepSeek story stands to be scrutinized even more carefully, the reframing of the problem statement, i.e. from „hardware“ to code, is a sobering realization. If the open-source community in the AI space continues to grow, the industry will essentially „democratize“ much faster. This doesn’t bode well for lofty forward valuations.

The fundamentals indicate that ARM is once again a highly-profitable company with solid industry connections and revenue channels. While the shift of focus to „code“ over hardware might dampen forward outlook, the fact remains that chipsets are still fundamental. In this particular part of the semiconductor industry, ARM is well-positioned.