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探索 AI 模型 33

为你发现值得关注的模型

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。

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ESMC-300M

biohub

ESMC is a state-of-the-art protein language model that has learned the rules of protein biology from training on billions of protein sequences. ESMC provides representations of proteins enabling novel AI applications from therapeutic protein engineering to unlocking basic insights into protein biology across life. The ESMC 6B model has 6 billion parameters, with 80 layers and 2.37e23 training flops. We additionally release overtrained 300M and 600M parameter variants of ESMC for local inference and finetuning. The ESMFold2 structure prediction models are trained on top of a frozen ESMC 6B language model. ESMFold2 is a state-of-the-art model for protein structure prediction and design that defines a new frontier for speed and accuracy.

译文排队中 · 当前显示来源原文

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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。

基础资料已收录 · 缺失资料后续补充

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 ↗

ESMC is a state-of-the-art protein language model that has learned the rules of protein biology from training on billions of protein sequences. ESMC provides representations of proteins enabling novel AI applications from therapeutic protein engineering to unlocking basic insights into protein biology across life. The ESMC 6B model has 6 billion parameters, with 80 layers and 2.37e23 training flops. We additionally release overtrained 300M and 600M parameter variants of ESMC for local inference and finetuning. The ESMFold2 structure prediction models are trained on top of a frozen ESMC 6B language model. ESMFold2 is a state-of-the-art model for protein structure prediction and design that defines a new frontier for speed and accuracy.

译文排队中 · 当前显示来源原文

填空与掩码
输入 文本→ 输出 文本
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 ↗

ESMC-600M

biohub

ESMC is a state-of-the-art protein language model that has learned the rules of protein biology from training on billions of protein sequences. ESMC provides representations of proteins enabling novel AI applications from therapeutic protein engineering to unlocking basic insights into protein biology across life. The ESMC 6B model has 6 billion parameters, with 80 layers and 2.37e23 training flops. We additionally release overtrained 300M and 600M parameter variants of ESMC for local inference and finetuning. The ESMFold2 structure prediction models are trained on top of a frozen ESMC 6B language model. ESMFold2 is a state-of-the-art model for protein structure prediction and design that defines a new frontier for speed and accuracy.

译文排队中 · 当前显示来源原文

填空与掩码
输入 文本→ 输出 文本
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 ↗

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。

基础资料已收录 · 缺失资料后续补充

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 ↗

ESMC is a state-of-the-art protein language model that has learned the rules of protein biology from training on billions of protein sequences. ESMC provides representations of proteins enabling novel AI applications from therapeutic protein engineering to unlocking basic insights into protein biology across life. The ESMC 6B model has 6 billion parameters, with 80 layers and 2.37e23 training flops. We additionally release overtrained 300M and 600M parameter variants of ESMC for local inference and finetuning. The ESMFold2 structure prediction models are trained on top of a frozen ESMC 6B language model. ESMFold2 is a state-of-the-art model for protein structure prediction and design that defines a new frontier for speed and accuracy.

译文排队中 · 当前显示来源原文

填空与掩码
输入 文本→ 输出 文本
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 ↗

ESMC-6B

biohub

ESMC is a state-of-the-art protein language model that has learned the rules of protein biology from training on billions of protein sequences. ESMC provides representations of proteins enabling novel AI applications from therapeutic protein engineering to unlocking basic insights into protein biology across life. The ESMC 6B model has 6 billion parameters, with 80 layers and 2.37e23 training flops. We additionally release overtrained 300M and 600M parameter variants of ESMC for local inference and finetuning. The ESMFold2 structure prediction models are trained on top of a frozen ESMC 6B language model. ESMFold2 is a state-of-the-art model for protein structure prediction and design that defines a new frontier for speed and accuracy.

译文排队中 · 当前显示来源原文

填空与掩码
输入 文本→ 输出 文本
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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