A $1,500, 1B-Parameter Breakthrough: Sapient Trains Efficient Reasoning AI
Sapient researchers trained a 1B-parameter HRM-Text foundation model from scratch for about $1,500 using a novel Hierarchical Recurrent Model that separates slow strategic reasoning from fast execution, and trains on instruction-response data instead of raw text. The result is competitive with larger open models on key benchmarks while using far less compute and data, suggesting enterprises can deploy compact, domain-tailored reasoning engines paired with external knowledge sources rather than relying on expensive, internet-scale pretraining. HRM-Text is presented as a proof-of-concept for affordable enterprise AI—not a plug-and-play ChatGPT replacement, but a lean core for task-specific reasoning with configurable retrieval and deployment workflows.