# ai-модели

Published articles for ai-модели.

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## Сравнение AI-систем для глубокого анализа данных и исследований

DevFeed: [Сравнение AI-систем для глубокого анализа данных и исследований](<https://devfeed.tech/articles/deep-research-showdown-ai-24010.md>)

Original publisher: [Read original article](<https://habr.com/ru/companies/redmadrobot/articles/891970/>)

Author: kekslop (red\_mad\_robot)

Published: 2025-03-18T12:40:03Z

Content type: comparison

Language: ru

Sources: [Redmadrobot EN](<https://devfeed.tech/sources/redmadrobot-en.md>), [Redmadrobot RU](<https://devfeed.tech/sources/redmadrobot-ru.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [Retrieval Augmented Generation (RAG)](<https://devfeed.tech/topics/retrieval-augmented-generation-rag.md>), [Langgraph](<https://devfeed.tech/topics/langgraph.md>), [vllm](<https://devfeed.tech/topics/vllm.md>), [OpenAI](<https://devfeed.tech/topics/openai.md>), [Claude](<https://devfeed.tech/topics/claude.md>)

Tags: [ai](<https://devfeed.tech/tags/ai.md>), [ai-6560afdd46fd](<https://devfeed.tech/tags/ai-6560afdd46fd.md>), [deepresearch](<https://devfeed.tech/tags/deepresearch.md>), [langgraph](<https://devfeed.tech/tags/langgraph.md>), [llm](<https://devfeed.tech/tags/llm.md>), [openai](<https://devfeed.tech/tags/openai.md>), [rag](<https://devfeed.tech/tags/rag.md>), [research](<https://devfeed.tech/tags/research.md>), [sast](<https://devfeed.tech/tags/sast.md>), [structured-output](<https://devfeed.tech/tags/structured-output.md>), [tag-1cd610c0e518](<https://devfeed.tech/tags/tag-1cd610c0e518.md>), [tag-5e27d5297aca](<https://devfeed.tech/tags/tag-5e27d5297aca.md>), [tag-8e9a901cca08](<https://devfeed.tech/tags/tag-8e9a901cca08.md>), [tag-baf5012a40ff](<https://devfeed.tech/tags/tag-baf5012a40ff.md>), [vllm](<https://devfeed.tech/tags/vllm.md>)

### AI overview

The article compares OpenAI, Grok, Perplexity, and the author's NDT Deep Research system on five analytical tasks, including financial-market analysis, technology research, and identifying promising AI startups. NDT Deep Research uses LangGraph, Tavily, multiple language models, Structured Output, vLLM, retrieval-augmented generation, and source analysis. The author reports that system changes reduced generation costs threefold and latency by 40%.

### Source excerpt

Как я сравнил топовые AI-модели для глубокого анализа данных и собственную разработку Привет! Меня зовут Валера Ковальский, я CEO NDT by red_mad_robot. Недавно я протестировал ведущие AI-системы, которые способны проводить глубокие исследования, и делюсь с вами результатами. Читать далее