DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model DeepSeek-AI research@deepseek.com Abstract We present DeepSeek-V2, a strong Mixture-of-Experts (MoE) language model model characterized by economical training and efficient inference. It comprises 236B total parameters, of which 21B are activated for each token, and supports a context length of 128K tokens. DeepSeek-V2 Key-Value (KV) cache into a latent vector, while DeepSeekMoE enables training strong models at an economical cost through sparse computation. Compared with DeepSeek 67B, DeepSeek-V2 achieves significantly

your company on-site for dynamic customized training where you already are - generally the most economical option for groups (DE, NL, RO, CZ, JP, US, PL, SE, …) 2. Come to a conference workshop C++ On your company on-site for dynamic customized training where you already are - generally the most economical option for groups (DE, NL, RO, CZ, JP, US, PL, SE, …) 2. Come to a conference workshop C++ On

resources, based on application requirements ü Monitor opportunities for more efficient and economical cloud resources ü Fully managed Low Cost 19 ©2018 VMware, Inc. VMware Kubernetes Engine: IT

application layer ● MySQL compatiblity Cons: ● Not 100% MySQL compatibility (full list here) ● Less economical when data is small ● Extra latency introduced by 2PC ● Relatively complex to deploy than standalone

crux of quantization is to trade off model precision for a smaller model size which results in economical storage and transmission. The mars rover example demonstrated this technique using an image of

more efficiently. SUSE Rancher charges per node and not per vCPU, providing transparent and economical pricing for users. Combined with a flexible and vendor-agnostic approach to Kubernetes, it is

useful for verse and addresses: | The limerick packs laughs anatomical | In space that is quite economical. | But the good ones I've seen | So seldom are clean | And the clean ones so seldom are comical

In his book The Coal Question, he noted ‘It is wholly a confusion of ideas to suppose that the economical use of fuel is equivalent to diminished consumption. The very contrary is the truth.’ AI Model

instances with relatively few CPU cores and lighter memory requirements, which tend to be more economical than running large instance sizes. Running Multiple Tablets Per Server If you are using physical

instances with relatively few CPU cores and lighter memory requirements, which tend to be more economical than running large instance sizes. Running Multiple Tablets Per Server If you are using physical