Looped models: scaling and practical evaluation
An article dated October 30, 2025 reports training looped language models with 2.6 billion parameters and more than 7 trillion tokens, with performance comparable to models two to three times larger.
Source: Escalando o raciocínio latente com modelos de linguagem em loop (x.com). Text prepared with AI from this source.
What happened and what to do
The article, published on October 30, 2025, reports that looped language models were scaled to 2.6 billion parameters and trained on more than 7 trillion tokens. The author says their performance was equivalent to that of state-of-the-art models two to three times larger.
A company interested in this architecture can begin by comparing it with its current solution on representative tasks, measuring quality, latency, cost, and infrastructure requirements. The consultancy can help set up this evaluation and, if viable, implement private inference and monitoring in the company’s environment.
How the consultancy can help
Wendelmaques can diagnose the opportunity, define evaluation criteria and scope, and implement and operate a proof of concept or an inference and monitoring solution on the client’s infrastructure.
Next step
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