Новая модель искусственного интеллекта DeepSeek, похоже, является одним из лучших конкурентов с открытым исходным кодом

The model, DeepSeek V3, was развитый by DeepSeek and released on Wednesday under a license that allows developers to download and modify it for most applications, including commercial ones.

DeepSeek V3 can handle a range of text-based workloads and tasks, such as coding, translation, essays, and emails based on descriptive prompts.

According to DeepSeek’s internal benchmarking, DeepSeek V3 outperforms both downloadable, “openly” available models and “closed” AI models that can only be accessed through the API. In the subset of programming competitions held on the Codeforces platform, DeepSeek outperforms other models, including Llama 3.1 405B by Мета, GPT-4o by OpenAI, and Qwen 2.5 72B by Alibaba.

DeepSeek V3 also outperforms competitors in the Aider Polyglot benchmark, designed to measure, among other things, whether a model can successfully write new code that integrates into existing code.

DeepSeek claims that DeepSeek V3 was trained on a dataset of 14.8 trillion tokens. In data science, tokens are used to represent bits of raw data – 1 million tokens equals about 750,000 words.

It’s not just the training set that’s massive. DeepSeek V3 is huge: 671 billion parameters, or 685 billion on the Hugging Face AI development platform. (Parameters are internal variables that models use to make predictions or decisions.) This is about 1.6 times more than Llama 3.1 405B, which has 405 billion parameters.

The number of parameters often (but not always) correlates with skill; models with more parameters tend to outperform models with fewer parameters. But large models also require more powerful hardware to run. An unoptimized version of DeepSeek V3 would need a bank of high-performance GPUs to answer questions at a reasonable