Step3-VL-10B

**STEP3-VL-10B** is a lightweight open-source foundation model designed to redefine the trade-off between compact efficiency and frontier-level multimodal intelligence. Despite its compact **10B parameter footprint**, STEP3-VL-10B excels in **visual perception**, **complex reasoning**, and **human-centric alignment**. It consistently outperforms models under the 10B scale and rivals or surpasses significantly larger open-weights models (**10×–20× its size**), such as GLM-4.6V (106B-A12B), Qwen3-VL-Thinking (235B-A22B), and top-tier proprietary flagships like Gemini 2.5 Pro and Seed-1.5-VL. Figure 1: Performance comparison of STEP3-VL-10B against SOTA multimodal foundation models. SeRe: Sequential Reasoning; PaCoRe: Parallel Coordinated Reasoning. 1. **Unified Pre-training on High-Quality Multimodal Corpus:** A single-stage, fully unfrozen training strategy on a 1.2T token multimodal corpus, focusing on two foundational capabilities: **reasoning** (e.g., general knowledge and education-centric tasks) and **perception** (e.g., grounding, counting, OCR, and GUI interactions). By jointly optimizing the Perception Encoder and the Qwen3-8B decoder, STEP3-VL-10B establishes intrinsic vision-language synergy. 2. **Scaled Multimodal Reinforcement Learning and Parallel Reasoning:** Frontier capabilities are unlocked through a rigorous post-training pipeline comprising two-stage supervised finetuning (SFT) and **over 1,400 iterations of RL** with both verifiable rewards (RLVR) and human feedback (RLHF). Beyond sequential reasoning, we adopt **Parallel Coordinated Reasoning (PaCoRe)**, which allocates test-time compute to aggregate evidence from parallel visual exploration.

译文尚未就绪，显示来源原文