ERNIE-5.0 Tops LMArena Text Leaderboard as No.1 Chinese Model!
On January 15, LMArena released its latest rankings. ERNIE-5.0-0110 achieved a score of 1,460, ranking No. 1 among Chinese models and No. 8 globally on the LMArena Text Arena.
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ERNIE-5.0-Preview-1220 Becomes the Sole Chinese Model in LMArena Vision Top 10!
On January 8, LMArena released its latest rankings. ERNIE-5.0-Preview-1220 achieved a score of 1226, ranking No. 1 in China and No. 8 globally on the LMArena Vision Arena.
Best Text model from China in LMArena is now ERNIE-5.0-Preview-1203!
Just now, LMArena released its latest rankings. Baidu’s ERNIE-5.0-Preview-1203 scored an impressive 1,451 points.
ERNIE-5.0-Preview-1103 landed on the LMArena Text Leaderboard!
We’ve just refreshed our standings with the latest ERNIE-5.0-Preview-1103 on LMArena. 🚀 ERNIE-5.0-Preview-1103 holds the top 20 in the most competitive Arena.
ERNIE-5.0-Preview-1120, ready for testing in LMArena!
ERNIE-5.0-Preview-1120 now ranks #1 in domestic on the LMArena Vision leaderboard
ERNIE-4.5-VL-28B-A3B-Thinking: A Breakthrough in Multimodal AI
We release ERNIE-4.5-VL-28B-A3B-Thinking, a multimodal reasoning model that achieves SOTA performance while activating only 3B parameters.
ERNIE-5.0-Preview-1022, ready for testing in LMArena!
ERNIE-5.0-Preview-1022 now ranks #2 globally on the LMArena Text leaderboard
PaddleOCR-VL: Boosting Multilingual Document Parsing via a 0.9B Ultra-Compact Vision-Language Model
We are excited to release PaddleOCR-VL, a SOTA and resource-efficient model tailored for document parsing.
ERNIE 4.5 Gets a Major Inference Speed Boost
How the new PLAS sparse attention update delivers performance gains for long-context inference on ERNIE 4.5 models.
FastDeploy 2.0: A Large-Scale Model Inference and Deployment Toolkit with Native Support for ERNIE 4.5
As large models such as the ERNIE 4.5 family continue to be open-sourced, interest in their inference performance and deployment efficiency has multiplied across both research and industry. FastDeploy 2.0, built on the PaddlePaddle framework, addresses this demand by offering an end-to-end toolkit for efficient deployment and high-performance inference of large models.