Almost Timely News: 🗞️ How to Build a Cheap AI Setup (2026-08-09)

Almost Timely News: 🗞️ How to Build a Cheap AI Setup (2026-08-09) :: View in Browser

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What’s On My Mind: How to Build a Cheap AI Setup

I’ve been putting together a new course for Trust Insights, AI for Writing (and Writers), which will be coming out August 25th, and during the process of creating that course, I realized I’ve never walked through setting up a discount agentic AI system.

For a while now, many of us who work in “corporate” have had access to what feels like unlimited amounts of AI (though that free ride is coming to an end at enterprise shops thanks to absurdly large bills). For the average person who doesn’t have the backing of a corporation, how could we tap into the power of agentic systems without tapping out our wallets?

This tracks back to a question from Leslie in the Analytics for Marketers Slack group:

“have you done a video or post with recommendations for a cheap second computer set up someone can use to build their separate AI machine?“

So this week, let’s get scrappy.

Warnings, Disclaimers, Disclosures

If you work at a company, please check with IT before installing software willy-nilly. As a former IT professional, we thank you.

Second, in this issue I’ll be talking about Chinese-made AI models like Qwen and DeepSeek. There is a HUGE difference between a Chinese model hosted by a company in the People’s Republic of China (PRC), and a Chinese-made model hosted by a company outside the PRC.

It is manifestly unsafe to use any AI models hosted in the PRC for any kind of confidential information, period. Totally fine to use those models for things that are completely public, like research requests.

However, it is completely safe to use Chinese-made AI models on your own hardware, or in an infrastructure that’s trustworthy. There are many, many great inference providers that have things like Zero Data Retention (ZDR) hosting which are even safer to use than Big Tech models because the providers warrant that they don’t keep your data at all. (Most Big Tech providers have a “we hold onto your data for 30 days to prevent abuse” clause in their Terms of Service)

There is a lot of fear mongering about open weights models (including the Chinese ones) happening right now because Big Tech providers’ profits are on the line if these models continue to offer parity of capabilities at a fraction of the cost. Don’t believe the hype; open weights models are so safe that companies like HuggingFace have used them to do their own cybersecurity defenses.

Third, where I have commercial relationships, I’ll disclose them. I have an Amazon affiliate link in this week’s article, and obviously I work for my company, Trust Insights. I do not have a financial interest in the other companies mentioned as of the time of writing. (but I’m happy to, call me)

Part 1: The Model

We’ll begin our tour with what model to use. In general, you want models that are a blend of cost efficient with effective performance. One of my favorite sites for this is Artificial Analysis; there’s a nice little grid on their models page that shows cost versus intelligence. What we’re looking for in this grid is models that are at the top left corner - the vertical (y) axis is brains, where higher is better, and the horizontal (x) axis is cost, where to the left is lower.

The current winner here is DeepSeek V4 Flash 0731, which has a crazy low cost and lots of brains, on par with OpenAI’s newest model, GPT-5.6 Luna. On the far right is Claude Opus 5, which has about 15% more brains but 40x the cost. The worst quadrant to be in is the lower right - high cost, low brains.

For the purposes of building the cheapest agentic system, DeepSeek is going to be your daily driver model.

Now, it’s worth pointing out, as I have in my book Almost Timeless: 48 Foundation Principles of Generative AI that a daily driver may not be the smartest model, but in terms of day to day work, a model like DeepSeek v4 Flash is going to get the job done most of the time. Here’s a bit of retrospective, by the way, putting DeepSeek on the same scale as all of OpenAI’s major models over the years to see where it stacks up in terms of brains.