目前已知的较为全面实用的模型有以下几种：
OpenAIFebruary 27,2025[heading1]1 Introduction[content]We’re releasing a research preview of OpenAI GPT-4.5,our largest and most knowledgeable model yet.Building on GPT-4o,GPT-4.5 scales pre-training further and is designed to be more general-purpose than our powerful STEM-focused reasoning models.We trained it using new supervision techniques combined with traditional methods like supervised fine-tuning(SFT)and reinforcement learning from human feedback(RLHF),similar to those used for GPT-4o.We conducted extensive safety evaluations prior to deployment and did not find any significant increase in safety risk compared to existing models.Early testing shows that interacting with GPT-4.5 feels more natural.Its broader knowledge base,stronger alignment with user intent,and improved emotional intelligence make it well-suited for tasks like writing,programming,and solving practical problems with fewer hallucinations.We’re sharing GPT-4.5 as a research preview to better understand its strengths and limitations.We’re still exploring its capabilities and are eager to see how people use it in ways we might not have expected.This system card outlines how we built and trained GPT-4.5,evaluated its capabilities,and strengthened safety,following OpenAI’s safety process and Preparedness Framework.
Kolors可以说是最近开源的文生图模型中最给力的一个了。从技术报告来看，改进也是很全面的，更强的中文文本编码器、机造的高质量文本描述、人标的高质量图片、强大的中文渲染能力，以及巧妙的noise schedule解决高分辨率图加噪不彻底的问题。可以说是目前主流的文生图训练技巧都用上了，实测效果也确实很不错。在看到Kling视频生成的强大表现，不得不让人赞叹快手的技术实力。
LLM看这里：[详解：DeepSeek深度推理+联网搜索目前断档第一](https://waytoagi.feishu.cn/wiki/D9McwUWtQiFh9sksz4ccmn4Dneg)关键点：1.统一Transformer架构，使用同一个模型就能完成图片理解，图片生成2.提供1B和7B两种规模，适配多元应用场景3.全面开源，支持商用，MIT协议，部署使用便捷4.Benchmark表现优异，能力更全面（上一个是智源开源的Emu3模型（7B）：https://huggingface.co/deepseek-ai/Janus-Pro-7B模型（1B）：https://huggingface.co/deepseek-ai/Janus-Pro-1B官方解释：Janus-Pro是一种新型的自回归框架，它统一了多模态理解和生成。它通过将视觉编码解耦为独立的路径来解决先前方法的局限性，同时仍然利用单一的统一Transformer架构进行处理。解耦不仅缓解了视觉编码器在理解和生成中的角色冲突，还增强了框架的灵活性。Janus-Pro超越了之前的统一模型，并匹配或超过了特定任务模型的性能。Janus-Pro的简单性、高灵活性和有效性使其成为下一代统一多模态模型的有力候选者。下载地址：https://github.com/deepseek-ai/Janus