vLLM团队推出首个“全模态”推理框架vLLM-Omni，将文本、图像、音频、视频的统一生成从概念验证变为可落地的代码。该框架采用解耦流水线架构，包括模态编码器（如ViT、Whisper）、LLM核心（沿用vLLM自回归引擎）和模态生成器（如DiT、Stable Diffusion），支持多模态输入与输出。开发者可通过GitHub和ReadTheDocs获取，并立即pip安装使用。
vLLM团队推出vLLM-Omni推理框架，支持文本、图像、音频和视频等多模态输入输出，旨在简化多模态推理过程，为新一代全模态模型提供强大支持。
清华大学等机构联合发布全球首个基于MCP架构的开源RAG框架UltraRAG2.1，通过YAML配置即可实现多模态智能检索系统的多阶段推理与评估，无需编程，显著降低技术门槛，推动检索增强生成技术发展。
蚂蚁数科在香港金融科技节推出“多语种多模态大模型训练框架”，旨在解决大模型在多语言环境的应用瓶颈。传统英文大模型在小语种中易出现语言错乱和推理混乱，限制全球化发展。该框架通过优化多语种处理能力，提升模型在多样化语言环境下的表现，推动AI技术更广泛高效地服务于全球各行业。
Openai
$2.8
输入tokens/百万
$11.2
输出tokens/百万
1k
上下文长度
Google
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$2.1
Xai
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$3.5
2k
-
Anthropic
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$525
200
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$7
$35
$17.5
$21
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$4
$16
$1
$10
256
Baidu
128
$6
$24
$2
$20
$8
$240
52
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