Ditching the cloud for local AI — how I use two mini PCs to process millions of tokens a day and save money on costly API fees
In comparison, Moonshot is opening up Kimi K3 to the wider world. As part of releasing the model weights to the public, it will allow companies and organizations to run the model themselves without using Moonshot's cloud services, making adoption easier and potentially cheaper.
But it won't be cheap, as Kimi K3 still needs serious hardware investment to get up and running, by virtue of its massive VRAM requirements alone.
As large companies with major AI deployments began to scale back their AI initiatives in 2026, there's been a growing concern that all that infrastructure everyone's been spending hundreds of billions of dollars on might not be needed. Meta just started selling excess compute in a pivot to cloud services, and xAI unloaded the entire compute capacity of Colossus 1 to Anthropic at a discounted rate.
But if Kimi K3 is the way the industry might go, hardware demands are unlikely to fall, and as Jevon's paradox suggests , greater efficiency is only likely to increase usage, not shrink it.
Those trillions of parameters need to be stored in memory, and Bloomberg's estimates suggest Kimi K3 will require close to 1.5 TB of memory. It would need masses of high-end Nvidia GPUs to deploy it effectively, making the number of companies and organizations that could actually run Kimi K3 at scale rather small.
So even those who do look to leverage Kimi K3 to reduce operating costs will still need powerful hardware, and specifically a lot of memory. This suggests that the major competition for cutting-edge models is not going to crater costs like we initially saw with DeepSeek R1 last year, which means memory makers are going to continue making money hand over fist, due to their outsized demand and limited supply.
But Chinese memory suppliers like CXMT are on the rise , and on track to eclipse Micron's DRAM wafer capacity by the end of the year. Smaller local AI models will also continue to be further optimized for domestic hardware, reducing the stranglehold that some large tech companies have on the AI supply chain.
Kimi K3 is an industry disruptor and is already raising questions over AI costs, capabilities, and access. It's shown that you don't need proprietary models locked to a specific service to achieve frontier-model capabilities. It's also cheaper to run, but Moonshot achieved this with a sparse model that still requires massive hardware investment to operate.
Even though Kimi K3 activates only a fraction of its trillions of parameters for each query, it still needs all of them to be stored. Deploying this model at scale requires substantial memory capacity, bandwidth, and interconnects, even if its compute demands aren't as strenuous.
The open-weight nature means it has very real potential to supplant usage away from Western frontier models in the short term, but it isn't about to change the story we've been told on required infrastructure. Kimi K3 needs the same kind of hardware to run as GPT 5.6 and Fable — which is likely to be far more of a limiting factor on its adoption than any kind of government blocks.
Jon Martindale is a contributing writer for Tom's Hardware. For the past 20 years, he's been writing about PC components, emerging technologies, and the latest software advances. His deep and broad journalistic experience gives him unique insights into the most exciting technology trends of today and tomorrow. ","collapsible":{"enabled":true,"maxHeight":250,"readMoreText":"Read more","readLessText":"Read less"}}), "https://slice.vanilla.futurecdn.net/13-4-25/js/authorBio.js"); } else { console.error('%c FTE ','background: #9306F9; color: #ffffff','no lazy slice hydration function available'); } Jon Martindale Freelance Writer Jon Martindale is a contributing writer for Tom's Hardware. For the past 20 years, he's been writing about PC components, emerging technologies, and the latest software advances. His deep and broad journalistic experience gives him unique insights into the most exciting technology trends of today and tomorrow.
Key considerations
- Investor positioning can change fast
- Volatility remains possible near catalysts
- Macro rates and liquidity can dominate flows
Reference reading
- https://www.tomshardware.com/tech-industry/artificial-intelligence/SPONSORED_LINK_URL
- https://www.tomshardware.com/tech-industry/artificial-intelligence/kimi-k3-rocks-the-ai-industry-as-moonshot-ai-undercuts-closed-source-american-competitors-on-price-but-the-huge-2-8t-open-weight-model-still-needs-serious-hardware-to-deploy-at-scale#main
- https://www.tomshardware.com/my-account
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