炸裂！太炸裂了！ 谷歌Nano Banana Pro一出世，全网都开始直呼： 这模型里到底装了什么鬼东西！ 硅谷VC大佬Deedy首先分享了自己的实测案例，看完只能说真不怪网友大惊小怪（doge）。 扔给它一份英伟达最新财报PDF文件，结果它秒秒钟生成了一张重点突出、内容精致的图表： 又或者直接将未加工的Graphviz图表代码丢给它，结果一次性就生成了带logo的可视化效果图: 更别提各种论文流程图、核心概念解释图了（连Transformer架构图都能AI直出）： 实测Nano Banana Pro 前情提醒，Nano Banana Pro是谷歌趁着Gemini 3 Pro好评如潮而推出的最新、最强文生图模型。 它又名Gemini 3 Pro Image，整合了Gemini 3 Pro的多模态理解能力以及谷歌搜索的知识库，能理解现实语义与物理逻辑。 其主要升级之处体现在： 目前，普通用户可以在Gemini应用中免费体验——选择"创建图像"功能时就能使用，不过免费用户有额度限制，超出后会回退到原始的Nano Banana模 型。Google AI Plus、Pro和Ultra订阅用户则享有更高的配额。 实测第 ...

时令 发自 凹非寺 量子位 | 公众号 QbitAI 全球文生图大模型王座，易主了。 就在刚刚，LMArena竞技场发布了最新的文生图榜单，第一名来自中国，属于 腾 讯混元图像 3.0 ！ | 用 | Overview | Text WebDev Vision | Text-to-Image | Image Edit | Search | Text-to-Video | Image-to-Video | Start Voting | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | હ | | | | | | | | | | ರಿಗ | | Text-to-Image Arena | | | Last Updated | | Total Votes | Total Models | | | | Compare LLMs based on their ability to generate images that match text descriptions. | | | Oct 4, 2025 | | 3,159,029 | 26 | | | ...

Core Viewpoint - Tencent has released and open-sourced HunyuanImage 3.0, the largest open-source native multimodal image generation model with 80 billion parameters, which integrates understanding and generation capabilities, rivaling leading closed-source models in the industry [1][20]. Model Features - HunyuanImage 3.0 supports multi-resolution image generation and exhibits strong instruction adherence, world knowledge reasoning, and text rendering capabilities, producing aesthetically pleasing and artistic outputs [1][11]. - The model inherits world knowledge reasoning from Hunyuan-A13B, allowing it to solve complex tasks such as generating detailed steps for solving equations [4][5]. - It can handle intricate prompts, such as visualizing sorting algorithms with specific styles and providing pseudocode, showcasing its advanced text rendering abilities [7][11]. Technical Architecture - The model is based on Hunyuan-A13B, utilizing a native multimodal and unified autoregressive framework that deeply integrates text understanding, visual understanding, and high-fidelity image generation [17][19]. - Unlike traditional approaches, HunyuanImage 3.0 employs a dual-encoder structure and incorporates generalized causal attention to enhance both language reasoning and global image modeling [22][25]. - The training process includes a three-stage filtering of over 10 billion images to select nearly 5 billion high-quality, diverse images, ensuring the removal of low-quality data [32]. Training Strategy - The training begins with a progressive four-stage pre-training process, gradually increasing image resolution and complexity, culminating in a fine-tuning phase focused on specific text-to-image generation tasks [36][38]. - The model employs a multi-stage post-training strategy that includes human preference data to refine the generated outputs [38]. Evaluation Metrics - HunyuanImage 3.0's performance is assessed using both automated metrics (SSAE) and human evaluations (GSB), demonstrating competitive results against leading models in the industry [40][46]. - The model achieved a 14.10% higher win rate compared to its predecessor, HunyuanImage 2.1, indicating significant improvements in performance [46].

Investment Rating - The report provides a positive investment outlook for the medical equipment sector, highlighting potential growth opportunities due to recent procurement trends and market recovery [1]. Core Insights - The medical equipment sector has shown a significant recovery in procurement since Q4 2024, with expectations for financial performance to reflect this recovery by Q3 2025 [1]. - The technology sector is expected to benefit from the commercialization of tier 1 generative models, which could lead to a revaluation of core business segments [1]. - The beverage industry, particularly Dongpeng Beverage, is experiencing strong sales growth, driven by new product launches and market expansion [1]. - The semiconductor equipment sector is seeing increased demand, with a focus on expanding production capabilities and meeting the needs of major clients [1]. - The aerospace and defense sector is positioned for growth as it aligns with national strategic goals, despite facing some operational challenges [1]. - The chemical sector is witnessing a recovery in performance, supported by favorable domestic policies and improving pricing power [1]. - The rare earth industry is expected to see significant growth due to rising demand in high-growth areas such as electric vehicles and robotics [1]. Summary by Category Medical Equipment - The report emphasizes the strong bidding performance of companies in the ultrasound and endoscopy segments, with notable growth in market share expected in 2025 [1]. Technology - The report highlights the potential for revenue growth driven by the deepening of platform capabilities and international expansion strategies [1]. Beverage - Dongpeng Beverage is noted for its rapid sales growth, with new product lines contributing to a more robust revenue stream [1]. Semiconductor Equipment - The report indicates that the company is transitioning from a focus on panel testing to semiconductor equipment, with expectations for significant revenue growth in this area [1]. Aerospace and Defense - The report outlines the strategic importance of the aerospace sector in national planning, with a focus on achieving operational goals despite regulatory challenges [1]. Chemicals - The report discusses the positive outlook for the chemical sector, driven by improved pricing and demand recovery [1]. Rare Earth - The report notes a substantial increase in production and sales in the rare earth sector, driven by strong demand in emerging technologies [1].

Core Viewpoint - Black Forest has released the developer version of the text-to-image model FLUX.1-Kontext, which allows users to edit images using natural language commands, positioning it as a strong competitor to existing models like OpenAI's GPT-image-1 [1] Group 1 - The FLUX.1-Kontext model enables one-click image editing similar to Photoshop through text input [1] - According to Black Forest's testing data, FLUX.1-Kontext outperforms OpenAI's latest text-to-image model in various evaluation benchmarks, including human preference assessment and instruction editing [1] - FLUX.1-Kontext is now considered one of the strongest open-source text-to-image models available [1]