谷歌于2026年6月发布开源语言模型DiffusionGemma，首次将图像AI扩散机制引入文本生成，打破传统逐字自回归范式。该模型从随机噪声迭代优化，并行输出256个词块。经英伟达优化，在单GPU单用户模式下，运行速度比同类传统模型快近四倍，如H100显卡处理单请求时表现显著提升。
腾讯微信AI团队推出新型扩散语言模型WeDLM，旨在提升文本生成效率。该模型结合扩散模型与因果注意力机制，通过拓扑重排技术兼容KV缓存，解决了传统扩散模型因双向注意力导致的推理效率问题，突破了GPT等大模型在并行推理上的限制。
字节跳动与南洋理工大学联合推出开源框架StoryMem，通过创新的“视觉记忆”机制，将单镜头视频扩散模型升级为多镜头长视频生成工具，能自动生成超过1分钟、镜头切换自然、角色场景连贯的叙事视频，推动开源AI视频技术向电影级叙事迈进。
清华大学TSAIL实验室与生数科技合作推出开源视频生成加速框架TurboDiffusion，通过集成SageAttention和稀疏线性注意力机制，显著降低高分辨率视频处理的计算开销，在保持生成质量的同时，将端到端扩散推理速度提升100至200倍。
高分辨率多视角扩散模型，使用高效行注意力机制。
Alibaba
-
Input tokens/M
Output tokens/M
Context Length
$2
256
Openai
$8.75
$70
400
$0.3
32
Tencent
$3
$9
16
Google
1k
Anthropic
$21
$105
200
131
Baichuan
$8
$1
01-ai
$0.99
Chatglm
nvidia
BR-RM是一种创新的两轮推理奖励模型，通过自适应分支和基于分支的反思机制，解决了传统奖励模型中的'判断扩散'问题，在多个奖励建模基准测试中取得了业界领先的性能。
fredzzp
Open-DCoder 0.5B 是一个基于Qwen2架构的代码生成掩码扩散模型，参数量为5亿。该模型采用双向注意力机制和创新的扩散生成方法，专门用于代码生成任务。
Runware
基于扩散的文本生成图像模型，支持自然语言和原生标签输入，采用v-prediction预测机制
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