AI NEWS · 模型情报站发现能力边界,让每一次选择更有依据 ↗基础档案先收录 · 缺失资料持续补齐
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找到适合你的 AI 模型。

从语言到影像,从开源到 API。读懂模型能力、比较真实成本,
为你的下一个想法,找到合适的智能引擎。

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84,991 款模型档案13202 家厂商 / 发布者45 个能力分类465 款有可比报价 · 30 款有公开评测
T文本生成▧图像生成▷视频生成⌘代码生成◖语音合成♫音乐生成⬡3D 建模▤文档分析
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探索 AI 模型 4

为你发现值得关注的模型

MAI-UI-2B

Tongyi-MAI

基础档案已收录,详细介绍后续补充。可先查看厂商、分类与来源。

分类待补充
输入 待核验→ 输出 待核验
价格待核验多模态与渠道费用须分别核对
查看详情 ↗
来源 / 文档 ↗

Z-Image

Tongyi-MAI

⚡️- Image An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer **Z-Image** is the foundation model of the ⚡️- Image family, engineered for good quality, robust generative diversity, broad stylistic coverage, and precise prompt adherence. While Z-Image-Turbo is built for speed, Z-Image is a full-capacity, undistilled transformer designed to be the backbone for creators, researchers, and developers who require the highest level of creative freedom. - **Undistilled Foundation**: As a non-distilled base model, Z-Image preserves the complete training signal. It supports full Classifier-Free Guidance (CFG), providing the precision required for complex prompt engineering and professional workflows. - **Aesthetic Versatility**: Z-Image masters a vast spectrum of visual languages—from hyper-realistic photography and cinematic digital art to intricate anime and stylized illustrations. It is the ideal engine for scenarios requiring rich, multi-dimensional expression. - **Enhanced Output Diversity**: Built for exploration, Z-Image delivers significantly higher variability in composition, facial identity, and lighting across different seeds, ensuring that multi-person scenes remain distinct and dynamic. - **Built for Development**: The ideal starting point for the community. Its non-distilled nature makes it a good base for LoRA training, structural conditioning (ControlNet) and semantic conditioning. - **Robust Negative Control**: Responds with high fidelity to negative prompting, allowing users to reliably suppress artifacts and adjust compositions.

译文排队中 · 当前显示来源原文

输入 文本→ 输出 图像
价格待核验多模态与渠道费用须分别核对
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来源 / 文档 ↗

Z-Image-Turbo

Tongyi-MAI

⚡️- Image An Efficient Image Generation Foundation Model with Single-Stream Diffusion Transformer Z-Image is a powerful and highly efficient image generation model family with **6B** parameters. Currently there are four variants: - 🚀 **Z-Image-Turbo** – A distilled version of Z-Image that matches or exceeds leading competitors with only **8 NFEs** (Number of Function Evaluations). It offers **⚡️sub-second inference latency⚡️** on enterprise-grade H800 GPUs and fits comfortably within **16G VRAM consumer devices**. It excels in photorealistic image generation, bilingual text rendering (English & Chinese), and robust instruction adherence.

译文排队中 · 当前显示来源原文

图像生成开放权重
输入 文本→ 输出 图像
价格待核验多模态与渠道费用须分别核对
查看详情 ↗
来源 / 文档 ↗
COST EXPLORER

好模型,也要算好成本。

费用分析

调整月度 Token 用量,直观比较不同模型的预估 API 开支。

1 M = 100 万 Token · 美元计价
仅比较同一渠道的基础文本 Token 报价

使用已采集且单位可比的 USD / 百万 Token 渠道报价。报价为采集时快照;不计缓存优惠、阶梯价、推理额外输出与税费,请以来源的当前报价为准。

MODEL HANDBOOK

读懂模型,再做选择

选型与常见问题
API 价格应该怎么比较?+

先区分输入、输出和缓存价格,再使用同一任务和用量估算总费用。图像、音频和视频可能按张、时长或分辨率计费,不能直接与 Token 单价比较。

开放权重,就代表可以免费商用吗?+

不一定。必须逐一核对具体模型版本的许可证、商用限制及使用政策。自己部署还需要考虑显存、推理资源和运维费用。

排行榜第一,就是最适合我的模型吗?+

榜单取决于测试任务、版本与评测方法。建议用实际业务样本比较准确性、时延、稳定性和成本,再选择模型。

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