Seed1.5-VL: ByteDance's Vision-Language Foundation Model Achieving 38 SOTA Benchmarks

Mon, 01 Jan 0001 00:00:00 +0000

In the rapidly advancing field of vision-language models, a new heavyweight has emerged from an unexpected corner. Seed1.5-VL, developed by ByteDance’s Seed team, has achieved state-of-the-art results on an astonishing 38 out of 60 public benchmarks, spanning image understanding, video comprehension, document parsing, and multi-image reasoning.

Built on a 20-billion parameter Mixture-of-Experts (MoE) architecture with approximately 2 billion activated parameters per token, Seed1.5-VL represents a careful balancing act between raw capability and computational efficiency. It outperforms models with far larger parameter counts while maintaining inference speeds suitable for real-world applications.

The model’s benchmark sweep is remarkable not just for the number of wins, but for the breadth of categories it dominates. From OCR and chart understanding to multi-image reasoning and video comprehension, Seed1.5-VL demonstrates that ByteDance’s research team has achieved something genuinely comprehensive in the multimodal space.

MoE on SoloSoft

Seed1.5-VL: ByteDance's Vision-Language Foundation Model Achieving 38 SOTA Benchmarks