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  • Large Language Models (LLMs) Ranking
  • Large Language Models
  • Close Source Models:
  • Open Source Models:
  • RAG
  • Fine Turning & More
  • Learning Resources:

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  1. INTO AI

Large Language Models (LLMs)

PreviousIndustry Reports and White PapersNextChatGPT

Last updated 19 days ago

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Large Language Models (LLMs) Ranking

Artificial Analysis

Independent analysis of AI language models and API. Provides quality, speed, and price comparisons.

LMArena.ai is a comprehensive AI model leaderboard, ranking over 240 large language models across various domains—including text, vision, web development, search, and coding—based on more than 3.5 million user votes.

Unlike traditional benchmarks, LMArena employs a crowdsourced, blind-voting system where users compare anonymous model responses to the same prompt and vote for the better one. This approach provides a dynamic, real-world evaluation of model performance.


Large Language Models

Close Source Models:

OpenAI's new o1 model, released on September 12, 2024, is now the most powerful LLM that can reason through complex problems by breaking them down into steps, excelling particularly in areas like mathematics, coding, and scientific reasoning where it outperforms previous models and even rivals human experts in some cases.

OpenAI o1 and o1 pro

GPT-4o-2024-08-06, OpenAI's most powerful LLM.

5/29/2024 ChatGPT with Gpt-4o is free for everyone

Elon Musk's AI company xAI officially launched Grok 3, touted as the "smartest AI on Earth," on February 18, 2025, claiming it surpasses previous models in reasoning and performance across various benchmarks.

Claude is a family of large language models developed by Anthropic, designed to generate natural, human-like responses to text and image-based inputs.

Anthropic introduced the new Claude 3.5 Sonnet, and Claude 3.5 Haiku.

Gemini 2.5

Open Source Models:

DeepSeek v3 is an advanced open-source large language model with 671 billion parameters, offering superior performance and cost-effectiveness, making it a formidable alternative to closed-source models from tech giants like OpenAI and Google.

LLama is a family of state-of-the-art large language models developed by Meta, designed to perform a wide range of natural language processing tasks with varying levels of computational efficiency and accuracy.

Llama 4

Llama 4 is Meta's latest open-weight multimodal AI model series featuring a Mixture of Experts architecture for efficient processing of text and images, with models like Scout offering a 10 million token context window and Maverick excelling in multilingual tasks.

Mistral AI offers a range of large language models (LLMs), both open source and commercial, designed for various tasks such as text generation, code generation, and multilingual reasoning.

Mistral Large 2

Mistral AI has introduced Mistral Large 2, a cutting-edge Language Model (LLM) that boasts state-of-the-art reasoning, knowledge, and coding capabilities, with a 128k context window and support for dozens of languages, including French, German, Spanish, Italian, Portuguese, Arabic, Hindi, Russian, Chinese, Japanese, and Korean, along with 80+ coding languages.

Qwen3 is the latest generation of large language models from Alibaba Cloud, featuring a hybrid approach to problem-solving with both "thinking" and "non-thinking" modes, support for 119 languages, and a range of model sizes-including dense and Mixture-of-Experts (MoE) architectures, designed for scalable, efficient, and multilingual AI applications.


RAG

Retrieval Augmented Generation (RAG) is a technique that enhances Large Language Models (LLMs) by retrieving relevant information from external knowledge sources to provide more accurate, up-to-date, and contextually appropriate responses

The all-in-one Desktop & Docker AI application with full RAG and AI Agent capabilities.

RAGFlow is an open-source RAG (Retrieval-Augmented Generation) engine based on deep document understanding.

Open-source RAG Framework for building GenAI Second Brains 🧠 Build productivity assistant (RAG) ⚡️🤖 Chat with your docs (PDF, CSV, ...) & apps using Langchain, GPT 3.5 / 4 turbo, Private, Anthropic, VertexAI, Ollama, LLMs, Groq that you can share with users ! Efficient retrieval augmented generation framework.

Retrieval Augmented Generation (RAG) chatbot powered by Weaviate


Fine Turning & More


Learning Resources:

Transformers, Explained: Understand the Model Behind GPT-3, BERT, and T5

What Is ChatGPT Doing … and Why Does It Work?

ChatGPT Prompt Engineering for Developers

LLM101n: Let's build a Storyteller

How GPT works

How I Use "AI" by Nicholas Carlini

Transformer Explainer

Generative AI Handbook: A Roadmap for Learning Resources

Anthropic courses

Deep Dive into LLMs like ChatGPT by Andrej Karpathy

How I use LLMs by Andrej Karpathy

Google - Prompt Engineering by Lee Boonstra

https://openai.com/index/learning-to-reason-with-llms/
https://claude.ai
https://deepmind.google/technologies/gemini/
https://github.com/deepseek-ai/DeepSeek-V3
https://ai.meta.com/blog/llama-4-multimodal-intelligence/
https://mistral.ai/
https://huggingface.co/Qwen/Qwen3-235B-A22B
https://github.com/Mintplex-Labs/anything-llm
https://github.com/infiniflow/ragflow
https://www.quivr.com
https://github.com/weaviate/Verba
https://daleonai.com/transformers-explained
https://writings.stephenwolfram.com/2023/02/what-is-chatgpt-doing-and-why-does-it-work/
https://www.deeplearning.ai/short-courses/chatgpt-prompt-engineering-for-developers/
https://github.com/karpathy/LLM101n
https://bbycroft.net/llm
https://nicholas.carlini.com/writing/2024/how-i-use-ai.html
https://poloclub.github.io/transformer-explainer/
https://genai-handbook.github.io
https://github.com/anthropics/courses/tree/master
https://youtu.be/7xTGNNLPyMI?si=6WfUHQx8-XqNxlQQ
https://youtu.be/EWvNQjAaOHw?si=bzp-Dy5yvnCohubp
https://www.kaggle.com/whitepaper-prompt-engineering

Meta Fine Turning Guide

Enterprise Guide to Building Intelligent AI Chatbots With RAG

ChatGPT Tutorial
LLama
Prompt Tutorial
Hallucination Problem

https://ai.meta.com/blog/how-to-fine-tune-llms-peft-dataset-curation/
https://www.nvidia.com/en-us/lp/ai-data-science/generative-ai/building-intelligent-ai-chatbots-with-rag-ebook/?ncid=pa-srch-goog-921287&wbraid=CmQKCAjwpvK4BhBuElQAC275K5Enwm5TbyBAJa9bTHOySqWuVbOOotxYcmXyq2DG8iG-VqmQeZ2vWWz8wWTs2HlOBi3Id8FSEYmB-nLapvZKxDS-t_tz9TbLINmy--__LHkaAmks&_bt=713058670066&_bk=&_bm=&_bn=&_bg=167350975575
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