Core Viewpoint - The article emphasizes the significance of the new multi-modal reasoning model, Step 3, released by Jumpshare, which fills a gap in the current AI landscape by combining strong reasoning capabilities with efficiency and open-source accessibility [4][5][25]. Group 1: Model Features - Step 3 is a 321 billion parameter MoE model with multi-modal reasoning capabilities, set to be officially open-sourced on July 31 [5][24]. - It achieved new state-of-the-art (SOTA) results in open-source multi-modal reasoning benchmarks [6]. - The model's reasoning decoding cost is only one-third of DeepSeek's, demonstrating superior efficiency [8]. Group 2: Market Trends - The industry is shifting towards multi-modal models, with reasoning capabilities becoming a focal point as generative AI enters a reasoning era [10]. - Efficiency, cost, and deployment friendliness are now critical factors in evaluating model performance, beyond just ranking [11][12]. Group 3: Innovations in Step 3 - Step 3 incorporates two key innovations: the AFD distributed reasoning system and the MFA attention mechanism, enhancing decoding efficiency and reducing reasoning costs [31][35]. - AFD separates Attention and FNN tasks to optimize resource usage, while MFA improves KV cache and computation efficiency [32][36]. Group 4: Cost Efficiency - Step 3's design allows it to operate with significantly lower costs compared to competitors, achieving a cost that is only 30% of DeepSeek-V3's on certain hardware [42]. - The model supports FP8 quantization, further reducing memory access and latency [41]. Group 5: Industry Collaboration - Jumpshare has initiated the "Model-Chip Ecological Innovation Alliance" with nearly ten chip and infrastructure partners to enhance model adaptability and computational efficiency [54][55]. - This collaboration aims to ensure that the model can run effectively on various hardware, including domestic chips [51][52]. Group 6: Application and Market Potential - Jumpshare's multi-modal reasoning model has been successfully integrated into various applications, including automotive and mobile devices, with significant interest from top manufacturers [60][69]. - The company anticipates a revenue of nearly 1 billion RMB in 2025, indicating a clear commercialization path for its technology [74].