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Baidu Releases ERNIE-4.5-21B-A3B-Thinking: A Compact MoE Model for Deep Reasoning

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Baidu AI Research team has just released ERNIE-4.5-21B-A3B-Thinking, a new reasoning-focused large language model designed around efficiency, long-context reasoning, and tool integration. Being part of the ERNIE-4.5 family, this model is a Mixture-of-Experts (MoE) architecture with 21B total parameters but only 3B active parameters per token, making it computationally efficient while maintaining competitive reasoning capability. […] The post Baidu Releases ERNIE-4.5-21B-A3B-Thinking: A Compact MoE Model for Deep Reasoning appeared first on MarkTechPost.

Scaling high-performance inference cost-effectively

At Google Cloud Next 2025, we announced new inference capabilities with GKE Inference Gateway, including support for vLLM on TPUs, Ironwood TPUs, and Anywhere Cache.  Our inference solution is based on AI Hypercomputer, a system built on our experience running…

Oldcastle accelerates document processing with Amazon Bedrock

This post explores how Oldcastle partnered with AWS to transform their document processing workflow using Amazon Bedrock with Amazon Textract. We discuss how Oldcastle overcame the limitations of their previous OCR solution to automate the processing of hundreds of thousands…