ERNIE 4.5 VL 424B A47B is Baidu's flagship multimodal foundation model in the ERNIE 4.5 family, designed for complex image-text understanding and visual reasoning. It uses a heterogeneous Mixture of Experts design that draws on 424 billion total parameters while activating 47 billion per token, with shared and dedicated parameters across textual and visual modalities routed through modality-isolated pathways. The architecture combines grouped-query attention in a deep stack of transformer layers with a sparse expert feed-forward network, and post-training layers supervised fine-tuning, preference optimization, and reinforcement learning with verifiable rewards on top of the base model.

In practical terms, the model is aimed at workflows that need long-context document analysis paired with image comprehension, where its extended context window supports extended inputs and its reasoning-oriented thinking mode helps with benchmarks tied to math, visual puzzles, and chart-style understanding. It is released as open weights under Apache 2.0, which lets teams self-host for privacy-sensitive workloads and tune the model to their own domains, and it is optimized for inference through vLLM with tensor parallelism across multiple accelerators. This combination of strong multimodal reasoning, open licensing, and scalable serving makes it a fit for enterprise search, content understanding, and research applications that require both visual perception and careful step-by-step analysis.