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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
THE AI MODEL DIRECTORY 模型探索，从这里开始

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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

This Text-to-Speech (TTS) model is provided solely for research, experimentation, and technology development purposes. Any audio content generated by the model does not represent the voice, identity, opinions, or endorsement of any real individual or organization. The authors and related parties assume no responsibility for any misuse, unlawful activities, violations of privacy, personality rights, intellectual property rights, or any direct or indirect damages arising from the use of this model. Users bear full responsibility and legal liability for the deployment, distribution, and use of the model. The use of this model for impersonation, voice cloning of individuals without lawful consent, creating misleading content, fraud, manipulation of public opinion, or any purpose that violates applicable laws is strictly prohibited. When using or sharing generated audio, it is strongly recommended to clearly disclose that the content is AI-generated and to comply fully with all applicable legal regulations, platform policies, and ethical standards. This model was trained entirely on **self-funded, personal hardware** — every GPU hour and electricity bill came out of my own pocket. If this work is useful to you, a small contribution helps cover the cost of the next training run and keeps future models free and open. Every coffee is hugely appreciated 🙏

译文排队中 · 当前显示来源原文

语音合成
输入 文本→ 输出 音频
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 ↗

The **Vietnamese Speech-to-Text (ASR)** model is built on the **ZipFormer architecture** — an improved variant of the Conformer — featuring only **30 million parameters** yet achieving **exceptional performance** in both speed and accuracy. On CPU, the model can transcribe a **12-second audio clip in just 0.3 seconds**, significantly faster than most traditional ASR systems without requiring a GPU. This model was trained entirely on **self-funded, personal hardware** — every GPU hour and electricity bill came out of my own pocket. If this work is useful to you, a small contribution helps cover the cost of the next training run and keeps future models free and open. Every coffee is hugely appreciated 🙏 You can try the model directly here: 👉 https://huggingface.co/spaces/hynt/k2-automatic-speech-recognition-demo

译文排队中 · 当前显示来源原文

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 ↗
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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