Core Insights - The Qianfan-VL series consists of three versions: 3B, 8B, and 70B, each designed for different application scenarios [1] - Qianfan-VL is a multimodal AI model capable of understanding both images and text, excelling in OCR and educational applications [3] - The model has been trained on Baidu's self-developed Kunlun chip P800, which offers significant advantages in power efficiency and performance [6][7] Model Specifications - The Qianfan-VL-3B has a context length of 32k and is suitable for real-time scenarios and OCR text recognition, while the 8B and 70B versions support server-side general scenarios and complex reasoning [2] - The 70B version achieved a near-perfect score of 98.76 in the ScienceQA test, outperforming several international competitors [4] Performance Comparison - In the Chinese multimodal benchmark CCBench, Qianfan-VL-70B scored 80.98, significantly higher than its peers, indicating a strong understanding of Chinese context [5] - The model excels in mathematical problem-solving tests, demonstrating a clear lead over competitors [5] Chip Technology - The Kunlun chip P800, which powers the Qianfan-VL model, features a unique XPU-R architecture that separates computing and communication units, enhancing efficiency [8] - The chip's power consumption ranges from 150W to 160W, making it more energy-efficient compared to competitors like NVIDIA A100 and H100 [7] Training Methodology - The training process involves a four-stage pipeline, including cross-modal alignment, general knowledge injection, domain-specific knowledge enhancement, and post-training for instruction following [10][14] - The model's training utilized a total of 2.66 trillion tokens of general knowledge data, ensuring a robust foundational understanding [14] Availability - The entire Qianfan-VL model series is open-sourced on platforms like GitHub and Hugging Face, allowing enterprises and developers to access and utilize the models freely [16]