I predict "The end of monster AI as we know it"

[usonian]

You can already run LLM models on home computers. Who here remembers mainframe computers?

And who runs financial models on them instead of using a spreadsheet for 99% of such chores?

OpenClaw on Mac. Secure by default. In one click.
https://holaclaw.ai/

Bring your own API key from any cloud provider - or skip the cloud entirely.

Five starting points — each with its own voice, style, and strengths.



Do you really need billion dollar data centers destroying the environment and raising electric costs for this upcoming cooling season?

And regarding those monster data centers:

How DeepSeek’s radical architecture is shattering Silicon Valley's token moat
https://venturebeat.com/infrastructure/how-deepseeks-radical-architecture-is-shattering-silicon-valleys-token-moat


This comes at a time when the closed Western labs, in particular OpenAI and Anthropic, face an intense return-on-investment scrutiny for their multi-billion dollar general-purpose hardware infrastructure investments.

DeepSeek’s announcement over the weekend that it has made its 75% price cut permanent on its flagship V4 Pro model is a disruptive assault on the capital-heavy business models of Silicon Valley’s frontier labs.

The reduction on DeepSeek V4 Pro directly undercuts comparable Western models used as workhorses for enterprise production. It is 7x cheaper on inputs and 17x cheaper on outputs than Anthropic’s Claude Sonnet or OpenAI’s GPT 5.5-Med, while the lightweight DeepSeek V4 Flash undercuts entry-tier alternatives like Claude Haiku by 10x to 25x.

snip

The price cuts are enabled by a series of hardware-software innovations, especially around cache, that make DeepSeek's models radically more efficient to run. When hosted natively in China, DeepSeek’s cache-read pricing is a whopping 87x cheaper than Western clouds — a deflationary floor so aggressive that handset giant Xiaomi just moved to match the exact pricing tier for its newly deployed MiMo architecture.

DeepSeek V4 Pro’s performance is ranked almost on par with Western frontier models, hitting 80.6% on coding-agent tasks via the SWE-bench Verified leaderboard and an elite reasoning score of 87.5 on the advanced MMLU-Pro technical index. Both V4 Pro and V4 Flash — a hyper-optimized speedy version for developers — are open-weight and issued under a permissive MIT license. This gives enterprises complete flexibility over deployment. This dual-model strategy allows technical teams to route their heaviest, multi-step autonomous agent workloads to the lightning-fast Flash model, while reserving the heavy Pro model for deep reasoning tasks, drastically lowering costs at a time when budget concerns have grown considerably.

Brute Force, The American Way?

It comes at a cost.

When "leaders" are just money-grubbing assholes.