Implications of DeepSeek on Global X AI & Innovative Technology Active ETF (3006) - Global X ETFs Hong Kong

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Implications of DeepSeek on
Global X AI & Innovative Technology Active ETF (3006)

By: Edward Chan

High-Performance Low-Cost Open Source LLM is Positive for AI Software and Applications

The launch of DeepSeek V3 further lowers the cost of LLM adoption. DeepSeek V3/R1 runs on lower inference cost with comparable performance vs leading models like Llama 3.1 405B / GPT4o and o1 (artificial analysis 2025). It is the leading model in terms of performance/cost. Startups leveraging these models, such as Perplexity and Glean, can achieve faster ROI by avoiding the prohibitive API fees associated with closed models and redirecting capital toward product differentiation and market penetration. Simultaneously, enterprise giants like Salesforce gain leverage to reduce dependency on costly closed-source APIs, accelerating in-house AI integration. We therefore turn more positive on the software sector and increase the funds exposure on the sector by adding weights on software names like Salesforce.

Too Early to Call for the End of the Scaling Law of Large Language Models

Our view is that while DeepSeek V3 demonstrate algorithmic and architecture innovation, it is too early to call the end of scaling law in LLM given the projected size of next-generation model training clusters. DeepSeek V3 is trained on 2048 H800 GPU over 60 days with a total cost of 5.6m USD, which is significantly lower verses other front-tier LLMs with similar performance. (DeepSeek 2025) GPT4 was trained on 25,000 NVIDIA A100 GPUs, Llama 3.1 was trained on 16,000 H100 GPUs, both likely cost 100s of millions to train.

However, note that the front-tier model today such as GPT4 is trained on last-generation NVIDIA chips (Ampere) with a relatively small cluster vs the size of investment we see today. It is important to recognize the time lag in infrastructure investment today and the launch of a new front-tier pre-trained model, i.e. the GPU investment today is used for models launching in 6 months to 1 year from now. We therefore keep our overweight in AI infrastructure play such as TSMC.

Lower Costs Increase Demand for Inference Compute

DeepSeek V3 launch significantly reduces the cost of inference, this creates a Jevons Paradox effect—when technological advancement results in efficiency improvement, overall demand increases as the cost of using the resource drops. This affordability encourages experimentation, expands use cases (e.g., high-volume tasks previously deemed uneconomical), and accelerates adoption across industries. The fund maintains its exposure to AI ASIC names such as Broadcom and MediaTek.

Global X AI & Innovative Technology Active ETF (2815 HK)
Listing Date 21 March 2022
Primary Exchange Hong Kong Stock Exchange
Ongoing Charges Over A Year1 0.75% p.a.
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Source: Mirae Asset; Data as of February 2025
1. The Fund adopts a single management fee structure, whereby a single flat fee will be paid out of the assets of the Fund to cover all of the costs, fees and expenses of the Fund. The ongoing charges figure is an annualised figure based on the ongoing expenses of the Fund, expressed as a percentage of the Fund’s average net asset value over the same period. It may be different upon actual operation of the Fund and may vary from year to year. As the Fund adopts a single management fee structure, the ongoing charges of the Fund will be equal to the amount of the single management fee, which is capped at 0.75% of the average Net Asset Value of the Fund. Any ongoing expenses exceeding 0.75% of the average Net Asset Value of the Fund will be borne by the Manager and will not be charged to the Fund. Please refer to the Product Key Facts and the Prospectus for further details.

Authored by:

Edward Chan

6 Feb 2025

Date : 6 Feb 2025

Category : Research & Insights

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