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An end-to-end open source machine learning platform. TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML powered applications. Build and train ML models easily using intuitive high-level APIs like Keras with eager execution, which makes for immediate model iteration and easy debugging. Easily train and deploy models in the cloud, on-prem, in the browser, or on-device no matter what language you use. A simple and flexible architecture to take new ideas from concept to code, to state-of-the-art models, and to publication faster. Build, deploy, and experiment easily with TensorFlow.

Dropbox Business is more than just secure file storage—it’s a smart workspace where teams, tools, and content come together. Create, store, and share cloud content from Google Docs, Sheets, and Slides, Microsoft Office files, and Dropbox Paper alongside traditional files in Dropbox. Dropbox Spaces brings your files and cloud content together, so that your PowerPoints can live next to your Google Docs, Trello boards, and whatever tools your team wants to use. Easily access your team’s work from your computer, mobile device, or any web browser. Keep your team’s files and the conversations about them in the same place by connecting tools like Slack and Zoom. Intelligently suggested files and folders keep your team one step ahead by giving everyone the content they need, when they need it. A secure, distributed infrastructure—plus admin tools for control and visibility—keep your company’s data safe on Dropbox.

Store, share, and access your files from any device. Your first 15 GB of storage are free. With Drive Enterprise, businesses only pay for the storage employees use. It comes with Google Docs, Sheets, and Slides — and works seamlessly with Microsoft Office. Keep photos, stories, designs, drawings, recordings, videos, and more. Your first 15 GB of storage are free with a Google Account. Your files in Drive can be reached from any smartphone, tablet, or computer. So wherever you go, your files follow. You can quickly invite others to view, download, and collaborate on all the files you want–no email attachment needed. Get started with Drive for free.

Mistral AI is a pioneering artificial intelligence startup specializing in open-source generative AI. The company offers a range of customizable, enterprise-grade AI solutions deployable across various platforms, including on-premises, cloud, edge, and devices. Flagship products include "Le Chat," a multilingual AI assistant designed to enhance productivity in both personal and professional contexts, and "La Plateforme," a developer platform that enables the creation and deployment of AI-powered applications. Committed to transparency and innovation, Mistral AI positions itself as a leading independent AI lab, contributing significantly to open-source AI and policy development.

DeepSeek Coder is a cutting-edge software tool designed to revolutionize the landscape of data analysis and coding. By leveraging advanced machine learning algorithms and natural language processing capabilities, it empowers users to seamlessly integrate data querying, analysis, and visualization into their workflow. The intuitive interface of DeepSeek Coder enables both novice and experienced programmers to efficiently write, test, and optimize code. Its robust set of features includes real-time syntax checking, intelligent code completion, and comprehensive debugging tools, all designed to streamline the coding process. Additionally, DeepSeek Coder's ability to understand and interpret complex data sets ensures that users can derive meaningful insights and create sophisticated data-driven applications with ease.

DeepSeek-R1 is an advanced open-source reasoning model developed by DeepSeek, designed to rival OpenAI's Model o1. Accessible via web, app, and API, it excels in complex tasks such as mathematics and coding, demonstrating superior performance on benchmarks like the American Invitational Mathematics Examination (AIME) and MATH. DeepSeek-R1 employs a mixture of experts (MoE) architecture with 671 billion total parameters, activating 37 billion parameters per token, enabling efficient and accurate reasoning capabilities. This model is part of DeepSeek's commitment to advancing artificial general intelligence (AGI) through open-source innovation.

Mistral 7B is a 7.3-billion-parameter language model that outperforms larger models like Llama 2 13B across various benchmarks. It employs Grouped-Query Attention (GQA) for faster inference and Sliding Window Attention (SWA) to efficiently handle longer sequences. Released under the Apache 2.0 license, Mistral 7B is accessible for deployment across diverse platforms, including local environments and major cloud services. Additionally, a fine-tuned version, Mistral 7B Instruct, demonstrates enhanced performance in instruction-following tasks, surpassing models like Llama 2 13B Chat.

Qwen2.5 is an advanced multimodal AI model designed to provide highly accurate and context-aware responses across a wide range of applications. It builds on the capabilities of its predecessors, integrating cutting-edge natural language understanding with enhanced reasoning, creativity, and multimodal processing. Qwen2.5 can seamlessly analyze and generate text, interpret images, and interact with complex data to deliver precise solutions in real time. Optimized for adaptability, it excels in personalized assistance, data analysis, creative content generation, and academic research, making it a versatile tool for professionals and everyday users alike. Its user-centric design emphasizes transparency, efficiency, and alignment with ethical AI practices.

We’ve integrated Llama 3 into Meta AI, our intelligent assistant, that expands the ways people can get things done, create and connect with Meta AI. You can see first-hand the performance of Llama 3 by using Meta AI for coding tasks and problem solving. Whether you're developing agents, or other AI-powered applications, Llama 3 in both 8B and 70B will offer the capabilities and flexibility you need to develop your ideas. With the release of Llama 3, we’ve updated the Responsible Use Guide (RUG) to provide the most comprehensive information on responsible development with LLMs. Our system-centric approach includes updates to our trust and safety tools with Llama Guard 2, optimized to support the newly announced taxonomy published by MLCommons expanding its coverage to a more comprehensive set of safety categories, code shield, and Cybersec Eval 2.

We introduce Codestral, our first-ever code model. Codestral is an open-weight generative AI model explicitly designed for code generation tasks. It helps developers write and interact with code through a shared instruction and completion API endpoint. As it masters code and English, it can be used to design advanced AI applications for software developers. Codestral is trained on a diverse dataset of 80+ programming languages, including the most popular ones, such as Python, Java, C, C++, JavaScript, and Bash. It also performs well on more specific ones like Swift and Fortran. This broad language base ensures Codestral can assist developers in various coding environments and projects.

The open source AI model you can fine-tune, distill and deploy anywhere. Our latest instruction-tuned model is available in 8B, 70B and 405B versions. Using our open ecosystem, build faster with a selection of differentiated product offerings to support your use cases. Choose from real-time inference or batch inference services. Download model weights to further optimize cost per token. Adapt for your application, improve with synthetic data and deploy on-prem or in the cloud. Use Llama system components and extend the model using zero shot tool use and RAG to build agentic behaviors. Leverage 405B high quality data to improve specialized models for specific use cases.

The open-source AI model you can fine-tune, distill and deploy anywhere is now available in more versions. Choose from 1B, 3B, 11B or 90B, or continue building with Llama 3.1. Llama 3.2 is a collection of large language models (LLMs) pretrained and fine-tuned in 1B and 3B sizes that are multilingual text only, and 11B and 90B sizes that take both text and image inputs and output text. Develop highly performative and efficient applications from our latest release. Use our 1B or 3B models for on device applications such as summarizing a discussion from your phone or calling on-device tools like calendar. Use our 11B or 90B models for image use cases such as transforming an existing image into something new or getting more information from an image of your surroundings.

SmolLM2 is a collection of state-of-the-art, compact language models developed for on-device applications. The models in this collection range from 1.7B parameters to smaller 360M and 135M versions, designed to perform efficiently even on less powerful hardware. These models excel in text generation tasks and are optimized for real-time, low-latency applications, providing high-quality results across various use cases, including content creation, coding assistance, and natural language processing. SmolLM2's flexibility makes it a suitable choice for developers looking to integrate powerful AI into mobile devices, edge computing, and other resource-constrained environments.

Qwen3, the latest iteration of the Qwen family of large language models, introduces groundbreaking features that enhance performance across coding, math, and general capabilities. With models like the Qwen3-235B-A22B and Qwen3-30B-A3B, Qwen3 achieves impressive results compared to top-tier models, thanks to its hybrid thinking modes that allow users to control the balance between deep reasoning and quick responses. The platform supports 119 languages and dialects, making it an ideal choice for global applications. Its pre-training process, which uses 36 trillion tokens, enables robust performance, and advanced reinforcement learning (RL) techniques continue to refine its capabilities. Available on platforms like Hugging Face and ModelScope, Qwen3 offers a powerful tool for developers and researchers working in diverse fields.

The next generation of our open source large language model. This release includes model weights and starting code for pretrained and fine-tuned Llama language models — ranging from 7B to 70B parameters. Llama 2 pretrained models are trained on 2 trillion tokens, and have double the context length than Llama 1. Its fine-tuned models have been trained on over 1 million human annotations. Llama 2 outperforms other open source language models on many external benchmarks, including reasoning, coding, proficiency, and knowledge tests. Llama 2 was pretrained on publicly available online data sources. The fine-tuned model, Llama-2-chat, leverages publicly available instruction datasets and over 1 million human annotations. We have a broad range of supporters around the world who believe in our open approach to today’s AI — companies that have given early feedback and are excited to build with Llama 2.

The TinyLlama project aims to pretrain a 1.1B Llama model on 3 trillion tokens. With some proper optimization, we can achieve this within a span of "just" 90 days using 16 A100-40G GPUs. We adopted exactly the same architecture and tokenizer as Llama 2. This means TinyLlama can be plugged and played in many open-source projects built upon Llama. Besides, TinyLlama is compact with only 1.1B parameters. This compactness allows it to cater to a multitude of applications demanding a restricted computation and memory footprint.

Transition seamlessly between eager and graph modes with TorchScript, and accelerate the path to production with TorchServe. Scalable distributed training and performance optimization in research and production is enabled by the torch-distributed backend. A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more. PyTorch is well supported on major cloud platforms, providing frictionless development and easy scaling. Select your preferences and run the install command. Stable represents the most currently tested and supported version of PyTorch. This should be suitable for many users. Preview is available if you want the latest, not fully tested and supported, 1.10 builds that are generated nightly. Please ensure that you have met the prerequisites (e.g., numpy), depending on your package manager. Anaconda is our recommended package manager since it installs all dependencies.

EXAONE is a large language model developed by LG AI Research with the goal of nurturing "Expert AI" in multiple domains. The Expert AI Alliance was formed as a collaborative effort among leading companies in various fields to advance the capabilities of EXAONE. Partner companies within the alliance will serve as mentors, providing skills, knowledge, and data to help EXAONE gain expertise in relevant domains. EXAONE, described as being akin to a college student who has completed general elective courses, requires additional intensive training to become an expert in specific areas. LG AI Research has already demonstrated EXAONE's abilities through real-world applications, such as Tilda, an AI human artist that debuted at New York Fashion Week, as well as AI applications for summarizing customer service conversations and extracting information from complex academic papers.