Is it worth buying an AI subscription?

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Subscriptions are becoming a first world problem and are often not worth it. Music and video subscriptions dominate users’ bank accounts, and now large AI language models (LLMs) do too. Free versions of big chatbots can get the job done, but if readers find their sensitive and personal data circulating in data centers disturbing, there is another solution.

Power AI users need more tokens or unlimited usage for agent features, reasoning models, image/video generation, but the average user will probably never reach the major free LLM limits. Serious users often subscribe to multiple AIs at once, and it adds up. ChatGPT Plus, Google AI Pro and Claude Pro cost around $20/month. Over a five-year period, that’s $1,200 out of pocket to use AI, and it’s even more for higher plans, like ChatGPT Pro ($6,000), Google AI Ultra ($5,999.40), and Claude Max ($6,000).

LLMs can run on a PC, as closed or open source models, and they are free. Combine one with an AI-enabled PC with two Ethernet ports to work with a user’s home network, and the possibilities are virtually endless. Open source solutions for the cost of a high-performance PC put privacy and control in the hands of DIYers, not in the hands of an AI or Cloud data center that ruins its local environment and harms residents.

Before discussing the hardware, it is essential to choose the right open source LLM to download. Open source templates are freely usable, editable, redistributable with no token or subscription fees and complete privacy peace of mind, with tasks performed locally and completely offline.

There are plenty to choose from, with the most popular choices being DeepSeek-V3/R1, Google Gemma 4, Z.ai GLM 5, Kimi K2.5, and MiniMax M2.5. Most run on consumer hardware, but the performance of these LLMs depends on the power of a user’s GPU and RAM. Free is nice, but the local AI cap is determined by local hardware specs. Subscription-based browser and app models using data center processing power.

DeepSeek is a good start, with general usage and reasoning models combining for solid, problem-solving performance. The easiest way to get it working is to download LM Studio and then follow the instructions to run a language model. For the average user who keeps their household privacy in mind, local open source AI is at a point where it is sufficient for daily questions, help, coding and much more. Most people think of AI as a solution, but it’s an effective tool, and my Radeon RX 9070 XT and 48GB of DDR5 RAM handle common family tasks quite well. But there are now mini PCs built around the use of AI.

I’ve played around with the capabilities of the GMKtec EVO-T2S, and it does everything needed to run a local language model. Featuring an Intel Core Ultra GMKtec EVO-T2S currently costs $3,299.99, which is a significant investment, but it’s not just about saving money by using AI.

Thanks to its 2.5GbE and 10GbE LAN port, GMKtec EVO-T2S can be integrated into a home network as a complete firewall and smart home hub also thanks to virtual machines. The best part is that it won’t cost a cent to set up. OPNsense is an excellent open source firewall operating system officially supported by Windows Hyper-V, just install it in a virtual machine.

This process can be used with another open source project called Home Assistant, which allows users to run their smart home functionality through their home network for ultimate privacy. DIYers can even install another M.2 SSD for more onboard storage alongside USB-C SSDs to run local storage on a home network.

By getting a purpose-built AI mini PC like the GMKtec EVO-T2S, users can save thousands of dollars in just a few years while making their home network more secure and functional. Generally speaking, AI subscriptions are not cost-effective and not worth it for most households.