Alternatives to Gemini 2.0 Flash Thinking

Hunyuan Turbo S by Tencent is an advanced AI model that integrates high-speed, real-time responses with deep analytical thinking. By improving the speed of text generation and minimizing delays, it provides faster and more intuitive answers, particularly in knowledge, math, and creative content. With its Hybrid-Mamba-Transformer architecture, Turbo S reduces computation costs, making it more efficient and scalable than traditional models. This hybrid approach offers the best of both fast thinking and slow, reasoned analysis, empowering businesses to deploy AI applications across a wide range of use cases, from simple queries to complex problem-solving.

Claude 3.7 Sonnet from Anthropic is an advanced AI model that offers a unique blend of fast responses and in-depth reflective reasoning. This hybrid approach allows users to toggle between speed and thoughtfulness, enabling the model to engage in complex problem-solving with precision. With its self-reflection mechanism, Claude 3.7 Sonnet is well-suited for tasks requiring deeper understanding and critical thinking, making it particularly valuable in fields like coding, research, and analysis. As an adaptable and powerful AI tool, it provides robust support for businesses and professionals needing sophisticated reasoning and reliable insights.

Gemini 2.0 Flash-Lite is Google DeepMind's most cost-efficient AI model, delivering strong performance while minimizing expenses. Designed for developers and businesses seeking an affordable AI solution, it supports multimodal inputs and offers a one-million-token context window for diverse applications. As the most budget-friendly option in the Gemini 2.0 family, Flash-Lite enables users to integrate advanced AI capabilities without high costs. Currently available in public preview, it provides an opportunity to explore its potential for enhancing AI-driven projects.

The Gemini 2.0 Flash AI represents the next-generation of high-speed intelligent computing. It is designed to set new standards in real-time decision-making and language processing. It builds on the solid foundation of its predecessor and incorporates enhanced neural technology and breakthrough advances in optimization to enable even faster and more accurate response times. Gemini 2.0 Flash was designed for applications that require instantaneous processing, adaptability, and live virtual assistants. Its lightweight and efficient design allows for seamless deployment across cloud and hybrid environments. Multitasking and improved contextual understanding make it an ideal tool to tackle complex and dynamic workflows.

Grok-3, created by xAI, marks a major leap forward in artificial intelligence, aiming to redefine standards in the field. As a multimodal AI, it is engineered to process and interpret diverse data types, including text, images, and audio, enabling seamless and comprehensive user interactions. Grok-3 was trained at an unparalleled scale, utilizing 100,000 Nvidia H100 GPUs on the Colossus supercomputer—ten times the computational resources of its predecessor. This massive processing capability positions Grok-3 to excel in tasks such as advanced reasoning, coding, and real-time analysis of current events via direct integration with X posts. With these advancements, Grok-3 is poised to surpass previous iterations and compete at the forefront of generative AI innovation.

Gemini 2.0 Pro is Google DeepMind’s cutting-edge AI model, built for advanced reasoning, coding, and problem-solving tasks. With a massive two-million-token context window, it can process extensive datasets with remarkable efficiency. One of its key strengths is its ability to integrate with external tools, such as Google Search and code execution environments, enabling more precise and informed responses. Currently in an experimental phase, Gemini 2.0 Pro pushes the boundaries of AI capabilities, making it a valuable asset for developers and researchers tackling complex challenges.

Gemini Flash, a large language model from Google, is specifically designed for low-latency, high-speed language processing tasks. Gemini Flash, part of Google DeepMind’s Gemini series is designed to handle large-scale applications and provide real-time answers. It's ideal for interactive AI experiences such as virtual assistants, live chat, and customer support. Gemini Flash is built on sophisticated neural structures that ensure contextual relevance, coherence, and precision. Google has built in rigorous ethical frameworks as well as responsible AI practices to Gemini Flash. It also equipped it with guardrails that manage and mitigate biased outcomes, ensuring alignment with Google's standards of safe and inclusive AI. Google's Gemini Flash empowers businesses and developers with intelligent, responsive language tools that can keep up with fast-paced environments.

Grok 3 Think represents a major leap forward in AI development, focusing on advanced reasoning capabilities that allow the model to tackle complex problems over extended periods. Through reinforcement learning, it can iteratively refine its solutions by reconsidering past steps, exploring new possibilities, and improving its approach. Trained on a massive scale, Grok 3 Think excels in areas like math, coding, and general knowledge, achieving remarkable results in high-level competitions like the American Invitational Mathematics Examination. It also stands out for its transparency, enabling users to examine the thought process behind its answers, setting a new standard for AI problem-solving and insight.

Gemini 2.0, an advanced AI model developed by Google is designed to offer groundbreaking capabilities for natural language understanding, reasoning and multimodal interaction. Gemini 2.0 builds on the success of Gemini's predecessor by integrating large language processing and enhanced problem-solving, decision-making, and interpretation abilities. This allows it to interpret and produce human-like responses more accurately and nuanced. Gemini 2.0, unlike traditional AI models, is trained to handle a variety of data types at once, including text, code, images, etc. This makes it a versatile tool that can be used in research, education, business and creative industries. Its core improvements are better contextual understanding, reduced biased, and a more effective architecture that ensures quicker, more reliable results. Gemini 2.0 is positioned to be a major step in the evolution AI, pushing the limits of human-computer interactions.

OpenAI o1 pro is an enhanced version of OpenAI’s o1 model. It was designed to handle more complex and demanding tasks, with greater reliability. It has significant performance improvements compared to its predecessor, the OpenAI o1 Preview, with a noticeable 34% reduction in errors and the ability think 50% faster. This model excels at math, physics and coding where it can provide accurate and detailed solutions. The o1 Pro mode is also capable of processing multimodal inputs including text and images. It is especially adept at reasoning tasks requiring deep thought and problem solving. ChatGPT Pro subscriptions offer unlimited usage as well as enhanced capabilities to users who need advanced AI assistance.

Gemini Advanced is an AI model that delivers unmatched performance in natural language generation, understanding, and problem solving across diverse domains. It features a revolutionary neural structure that delivers exceptional accuracy, nuanced context comprehension, and deep reason capabilities. Gemini Advanced can handle complex and multifaceted tasks. From creating detailed technical content to writing code, to providing strategic insights and conducting in-depth analysis of data, Gemini Advanced is designed to handle them all. Its adaptability, scalability and flexibility make it an ideal solution for both enterprise-level and individual applications. Gemini Advanced is a new standard in AI-powered solutions for intelligence, innovation and reliability. Google One also includes 2 TB of storage and access to Gemini, Docs and more. Gemini Advanced offers access to Gemini Deep Research. You can perform real-time and in-depth research on virtually any subject.

Grok 3 DeepSearch is a revolutionary AI model that enhances reasoning by incorporating deep search mechanisms, enabling the AI to delve into complex problems and explore various possibilities. As an AI agent, it can engage in extended reasoning, continuously testing and refining solutions, making it perfect for high-stakes tasks that require detailed problem-solving and critical thinking. Whether solving intricate math problems, generating code, or conducting thorough academic research, Grok 3 DeepSearch provides an elevated approach by leveraging real-time exploration and error correction. This model represents a significant leap forward in AI's ability to handle nuanced challenges in fields ranging from mathematics to software development and beyond.

DeepSeek-V3 is an advanced AI model built to excel in natural language comprehension, sophisticated reasoning, and decision-making across a wide range of applications. Harnessing innovative neural architectures and vast datasets, it offers exceptional capabilities for addressing complex challenges in fields like research, development, business analytics, and automation. Designed for both scalability and efficiency, DeepSeek-V3 empowers developers and organizations to drive innovation and unlock new possibilities with state-of-the-art AI solutions.

Marco-o1 is an advanced AI model that is designed for high-performance problem solving and natural language processing. It is designed to deliver precise, contextually rich answers by combining deep language understanding with a streamlined architectural design for speed and efficiency. Marco-o1 is a versatile AI system that excels at a wide range of tasks, including conversational AI. It also excels at content creation, technical assistance, and decision-making. It adapts seamlessly to the needs of diverse users. Marco-o1 is a cutting edge solution for individuals and organisations seeking intelligent, adaptive and scalable AI tools. It focuses on intuitive interactions, reliability and ethical AI principles. MCTS allows for the exploration of multiple reasoning pathways using confidence scores derived by softmax-applied logging probabilities of the top k alternative tokens. This guides the model to optimal solution.

Inflection AI, a leading artificial intelligence research and technology company, focuses on developing advanced AI systems that interact with humans more naturally and intuitively. The company was founded in 2022 by entrepreneurs like Mustafa Suleyman (one of the cofounders of DeepMind) and Reid Hoffman (co-founder of LinkedIn). Its mission is to make powerful AI accessible and aligned to human values. Inflection AI is a company that specializes in creating large-scale language systems to enhance human-AI interaction. It aims to transform industries from customer service to productivity by designing AI systems that are intelligent, responsive and ethical. The company's focus is on safety, transparency and user control to ensure that their innovations are positive for society while addressing the potential risks associated with AI.

OpenAI o1 is a new series AI models developed by OpenAI that focuses on enhanced reasoning abilities. These models, such as o1 preview and o1 mini, are trained with a novel reinforcement-learning approach that allows them to spend more time "thinking through" problems before presenting answers. This allows o1 excel in complex problem solving tasks in areas such as coding, mathematics, or science, outperforming other models like GPT-4o. The o1 series is designed to tackle problems that require deeper thinking processes. This marks a significant step in AI systems that can think more like humans.

Gemma is the family of lightweight open models that are built using the same research and technology as the Gemini models. Gemma was developed by Google DeepMind, along with other teams within Google. The name is derived from the Latin gemma meaning "precious stones". We're also releasing new tools to encourage developer innovation, encourage collaboration, and guide responsible use of Gemma model. Gemma models are based on the same infrastructure and technical components as Gemini, Google's largest and most powerful AI model. Gemma 2B, 7B and other open models can achieve the best performance possible for their size. Gemma models can run directly on a desktop or laptop computer for developers. Gemma is able to surpass much larger models in key benchmarks, while adhering our rigorous standards of safe and responsible outputs.

OpenAI o3 has been designed to improve reasoning by breaking complex instructions down into smaller, easier-to-understand steps. It is a significant improvement over previous AI versions, excelling at coding tasks, competitive programing, and achieving high marks in mathematics and science benchmarks. OpenAI o3 is a widely-used AI-driven decision-making and problem-solving tool that supports advanced AI. The model uses deliberative alignment to ensure that its responses are in line with established safety and ethics guidelines. This makes it a powerful tool, especially for developers, researchers and enterprises looking for sophisticated AI solutions.

The Gemini 1.5 Pro AI Model is a state of the art language model that delivers highly accurate, context aware, and human like responses across a wide range of applications. It excels at natural language understanding, generation and reasoning tasks. The model has been fine-tuned to support tasks such as content creation, code-generation, data analysis, or complex problem-solving. Its advanced algorithms allow it to adapt seamlessly to different domains, conversational styles and languages. The Gemini 1.5 Pro, with its focus on scalability, is designed for both small-scale and enterprise-level implementations. It is a powerful tool to enhance productivity and innovation.

The Gemini 1.5 Flash AI is a high-speed, advanced language model that has been designed for real-time responsiveness and lightning-fast processing. It is designed to excel in dynamic, time-sensitive applications. It combines streamlined neural technology with cutting-edge optimization methods to deliver exceptional performance and accuracy. Gemini 1.5 Flash was designed for scenarios that require rapid data processing, instant decisions, and seamless multitasking. It is ideal for chatbots and customer support systems. Its lightweight but powerful design allows it to be deployed efficiently on a variety of platforms, including cloud-based environments and edge devices. This allows businesses to scale operations with unmatched flexibility.

The o3-mini-high model from OpenAI represents a significant leap in AI reasoning capabilities, building on the foundation laid by its predecessor, the o1 series. This model is finely tuned for tasks requiring deep reasoning, particularly in coding, mathematics, and complex problem-solving scenarios. It introduces an adaptive thinking time feature, allowing users to tailor the AI's processing efforts to match the complexity of the task, with options for low, medium, and high reasoning modes. o3-mini-high has been reported to outperform o1 models on various benchmarks, including Codeforces, where it achieved a notable 200 Elo points higher than o1. It offers a cost-effective solution with performance that rivals higher-end models, maintaining the speed and accuracy needed for both casual and professional use. This model is part of the o3 family, which is designed to push the boundaries of AI's problem-solving abilities while ensuring that these advanced capabilities are accessible to a broader audience, including through a free tier and enhanced usage limits for Plus subscribers.

Language and its role as a means of demonstrating and facilitating understanding - or intelligence, as it is sometimes called - are fundamental to being human. It allows people to express themselves, build memories, and communicate ideas. These are the foundational components of social intelligence. Our teams at DeepMind are interested in the language processing and communication aspects, both for artificial agents and humans. As part of an broader portfolio of AI Research, we believe that the development and study more powerful language models, systems that predict and create text, have tremendous potential to build advanced AI systems. These systems can be used safely and effectively to summarise and provide expert advice, and follow instructions using natural language. Research is needed to determine the potential risks and benefits of language models before they can be developed.

OpenAI o3 Mini is a lightweight version o3 AI model that offers powerful reasoning capabilities, but in a more accessible and efficient package. O3-mini is designed to break complex instructions down into smaller, more manageable steps. It excels at coding tasks, competitive programing, and problem solving in mathematics and sciences. This compact model offers the same high level of precision and logic that its larger counterpart, but with reduced computation requirements. It is ideal for use in resource constrained environments. The o3 mini's deliberative alignment ensures ethical, safe and context-aware decisions. This makes it a versatile tool that can be used by developers, researchers and businesses looking for a balance between performance, efficiency and safety.

OpenAI o1 mini is a new and cost-effective AI designed to enhance reasoning, especially in STEM fields such as mathematics and coding. It is part of the o1 Series, which focuses on solving problems by spending more "thinking" time through solutions. The o1 mini is 80% cheaper and smaller than its sibling. It performs well in coding and mathematical reasoning tasks.

DeepSeek R2 is poised to succeed DeepSeek R1, the revolutionary AI reasoning model introduced in January 2025 by the Chinese AI startup DeepSeek. R1 made waves in the industry with its cost-efficient performance, competing with top models like OpenAI’s o1, and R2 is expected to push the boundaries even further. Designed for superior speed and human-like reasoning, it aims to excel in complex domains such as advanced programming and intricate mathematical problem-solving. By harnessing DeepSeek’s cutting-edge Mixture-of-Experts framework and optimized training strategies, R2 is set to surpass its predecessor while maintaining efficiency. Additionally, it may extend its capabilities beyond English, broadening its reach.

Gemini-Exp-1206 is an advanced AI model now available for early access to Gemini Advanced subscribers. Designed to excel in areas like programming, complex problem-solving, reasoning, and following intricate instructions, it pushes the boundaries of AI capabilities. This preview version offers users a glimpse into its powerful features, though some functionalities may still be refined. While real-time data access is not yet included, Gemini-Exp-1206 can be easily accessed via the Gemini model selection on both desktop and mobile platforms.

Open R1 is an open-source, community-driven initiative that aims to replicate the advanced AI capabilities found in DeepSeek-R1 using transparent methodologies. Open R1 AI Model or DeepSeek R1 online chat is available for free on Open R1. The project provides a comprehensive implementation, under the MIT licence, of DeepSeek's reasoning optimized training pipeline. This includes tools for GRPO-training, SFT-fine-tuning and synthetic data generation. Open R1 offers the entire toolchain to users, allowing them to create and fine-tune models using their own data.

Sky-T1-32B is an open-source reasoning tool developed by the NovaSky group at UC Berkeley’s Sky Computing Lab. It is comparable to proprietary models such as o1 preview on reasoning and coding tests, but was trained for less than $450. This shows the feasibility of cost-effective high-level reasoning abilities. The model was fine-tuned using Qwen2.5 32B-Instruct and a curated dataset with 17,000 examples from diverse domains including math and coding. The training took 19 hours using eight H100 GPUs and DeepSpeed Zero-3 offloading. All aspects of the project are open-source including the data, code and model weights. This allows the academic and open source communities to duplicate and enhance the performance.

DeepSeek-V2, developed by DeepSeek-AI, is a cutting-edge Mixture-of-Experts (MoE) language model designed for cost-effective training and high-speed inference. Boasting a massive 236 billion parameters—though only 21 billion are active per token—it efficiently handles a context length of up to 128K tokens. The model leverages advanced architectural innovations such as Multi-head Latent Attention (MLA) to optimize inference by compressing the Key-Value (KV) cache and DeepSeekMoE to enable economical training via sparse computation. Compared to its predecessor, DeepSeek 67B, it slashes training costs by 42.5%, shrinks the KV cache by 93.3%, and boosts generation throughput by 5.76 times. Trained on a vast 8.1 trillion token dataset, DeepSeek-V2 excels in natural language understanding, programming, and complex reasoning, positioning itself as a premier choice in the open-source AI landscape.

Doubao, an intelligent language model created by ByteDance, is a powerful tool for learning new languages. It has provided users with useful answers and insights on a wide range topics. Doubao is able to handle complex questions and provide detailed explanations. It can also engage in meaningful conversation. Its advanced language understanding and generation abilities continue to help people solve problems, explore new ideas, and seek knowledge. Doubao can be used for academic inquiries, inspiration for creative projects, or just a simple conversation.

QwQ-Max-Preview introduces an exciting glimpse into the capabilities of the Qwen2.5-Max-based AI model, optimized for advanced reasoning tasks, complex mathematics, coding, and agent-driven workflows. As a preview version, it showcases the model’s ability to process and provide solutions for diverse problems, setting the stage for the full release. The model is designed for deep learning tasks and promises further enhancements, with the official open-source release planned under the Apache 2.0 license. Future updates include the Qwen Chat app for seamless, user-friendly interaction and the availability of smaller models like QwQ-32B, which are ideal for developers and privacy-sensitive applications.

Llama 3.3, the latest in the Llama language model series, was developed to push the limits of AI-powered communication and understanding. Llama 3.3, with its enhanced contextual reasoning, improved generation of language, and advanced fine tuning capabilities, is designed to deliver highly accurate responses across diverse applications. This version has a larger dataset for training, refined algorithms to improve nuanced understanding, and reduced biases as compared to previous versions. Llama 3.3 excels at tasks such as multilingual communication, technical explanations, creative writing and natural language understanding. It is an indispensable tool for researchers, developers and businesses. Its modular architecture enables customization in specialized domains and ensures performance at scale.

Inception Labs has introduced Mercury, a game-changing diffusion-based large language model (dLLM) that sets new standards in speed, efficiency, and accuracy. Unlike traditional LLMs, Mercury generates text in a coarse-to-fine manner, allowing for real-time corrections and more structured outputs. This breakthrough model delivers over 1000 tokens per second, surpassing existing LLMs in both speed and computational cost efficiency. The Mercury Coder variant is optimized for code generation, achieving top-tier performance on industry benchmarks while being 5-10x faster than conventional coding AI models like GPT-4o Mini and Claude 3.5 Haiku. Mercury is now available via API and enterprise deployments, redefining AI-powered workflows.

GPT-4, a large multimodal (accepting text and image inputs) model that can solve complex problems with greater accuracy thanks to its advanced reasoning abilities and broader general knowledge than any of our other models. GPT-4 can be found in the OpenAI API for paying customers. GPT-4, like gpt 3.5-turbo is optimized for chat, but also works well with traditional completion tasks using the Chat Completions API. Our GPT guide will teach you how to use GPT-4. GPT-4 is a newer GPT-4 model that features improved instruction following, JSON Mode, reproducible outputs and parallel function calls. Returns up to 4,096 tokens. This preview model has not yet been adapted for production traffic.

GPT-4.5 marks a significant leap in AI model development, offering more accurate and nuanced text generation through an advanced combination of unsupervised learning and scalable training methods. This model is fine-tuned to interpret human cues with greater emotional intelligence (EQ) and creativity, excelling in tasks like writing assistance, content creation, and complex problem-solving. GPT-4.5 offers improved steerability and an ability to collaborate more naturally with humans, making it ideal for use in educational, business, and creative applications. The latest version is designed to reduce hallucinations and enhance overall reliability, while excelling in practical applications across various industries.

Qwen2.5, an advanced multimodal AI system, is designed to provide highly accurate responses that are context-aware across a variety of applications. It builds on its predecessors' capabilities, integrating cutting edge natural language understanding, enhanced reasoning, creativity and multimodal processing. Qwen2.5 is able to analyze and generate text as well as interpret images and interact with complex data in real-time. It is highly adaptable and excels at personalized assistance, data analytics, creative content creation, and academic research. This makes it a versatile tool that can be used by professionals and everyday users. Its user-centric approach emphasizes transparency, efficiency and alignment with ethical AI.

Gemini is multimodal by default, giving you the ability to transform any input into any output. We built Gemini responsibly, incorporating safeguards from the beginning and working with partners to make it more inclusive and safer. Integrate Gemini models in your applications using Google AI Studio and Google Cloud Vertex AI.

IBM® Granite™ is an AI family that was designed from scratch for business applications. It helps to ensure trust and scalability of AI-driven apps. Granite models are open source and available today. We want to make AI accessible to as many developers as we can. We have made the core Granite Code, Time Series models, Language and GeoSpatial available on Hugging Face, under a permissive Apache 2.0 licence that allows for broad commercial use. Granite models are all trained using carefully curated data. The data used to train them is transparent at a level that is unmatched in the industry. We have also made the tools that we use available to ensure that the data is of high quality and meets the standards required by enterprise-grade applications.

Google's Gemini Nano is a lightweight and energy-efficient AI model that delivers high performance even in environments with limited resources. Gemini Nano is a lightweight, energy-efficient AI model designed for edge computing and mobile apps. It combines Google's advanced AI with cutting-edge techniques to deliver seamless performance. It excels at tasks such as voice recognition, natural-language processing, real time translation, and personalized suggestions despite its small size. Gemini Nano is a local data processor that focuses on privacy and efficiency. This minimizes reliance on cloud infrastructure, while maintaining robust security. Its adaptability, low power consumption, and robust security make it a great choice for smart devices and IoT ecosystems.

Google's Gemini Deep Research is an AI-driven tool designed to enhance web-based research by automating complex information gathering and analysis. It utilizes advanced reasoning and contextual understanding to assist users in exploring in-depth topics, compiling structured reports, and summarizing key insights. By autonomously navigating multiple research steps, it collects relevant data from various sources and presents organized findings along with direct links for further exploration. This tool streamlines the research process, saving users time while ensuring comprehensive coverage of their topics. Available to Gemini Advanced subscribers, it provides an efficient way to synthesize vast amounts of information with AI-powered assistance.

You can use advanced language models and coding to solve a variety of problems. To build cutting-edge applications, leverage large-scale, generative AI models that have deep understandings of code and language to allow for new reasoning and comprehension. These coding and language models can be applied to a variety use cases, including writing assistance, code generation, reasoning over data, and code generation. Access enterprise-grade Azure security and detect and mitigate harmful use. Access generative models that have been pretrained with trillions upon trillions of words. You can use them to create new scenarios, including code, reasoning, inferencing and comprehension. A simple REST API allows you to customize generative models with labeled information for your particular scenario. To improve the accuracy of your outputs, fine-tune the hyperparameters of your model. You can use the API's few-shot learning capability for more relevant results and to provide examples.

DeepSeek-R1 is a cutting-edge open-source reasoning model crafted by DeepSeek, designed to compete with leading models like OpenAI's o1. Available through web platforms, applications, and APIs, it excels in tackling complex challenges such as mathematics and programming. With outstanding performance on benchmarks like the AIME and MATH, DeepSeek-R1 leverages a mixture of experts (MoE) architecture, utilizing 671 billion total parameters while activating 37 billion parameters per token for exceptional efficiency and accuracy. This model exemplifies DeepSeek’s dedication to driving advancements in artificial general intelligence (AGI) through innovative and open source solutions.

Phi-2 is a 2.7-billion-parameter language-model that shows outstanding reasoning and language-understanding capabilities. It represents the state-of-the art performance among language-base models with less than thirteen billion parameters. Phi-2 can match or even outperform models 25x larger on complex benchmarks, thanks to innovations in model scaling. Phi-2's compact size makes it an ideal playground for researchers. It can be used for exploring mechanistic interpretationability, safety improvements or fine-tuning experiments on a variety tasks. We have included Phi-2 in the Azure AI Studio catalog to encourage research and development of language models.

Inception Labs is redefining language model performance with its diffusion-based large language models (dLLMs), delivering unparalleled speed, efficiency, and precision. Unlike traditional models that generate text token-by-token, Inception’s dLLMs refine an initial noisy output into structured, high-quality responses. This innovation results in faster processing, reduced computational costs, and superior multimodal capabilities, making it ideal for complex reasoning, AI agents, and structured text generation. With its first commercial-scale model, Mercury, Inception is pushing AI to the next frontier, offering organizations and developers an advanced tool for next-gen AI applications.

As a tribute for Archimedes' 2311th birthday, which we celebrate this year, we release our first Mathstral 7B model, designed specifically for math reasoning and scientific discoveries. The model comes with a 32k context-based window that is published under the Apache 2.0 License. Mathstral is a tool we're donating to the science community in order to help solve complex mathematical problems that require multi-step logical reasoning. The Mathstral release was part of a larger effort to support academic project, and it was produced as part of our collaboration with Project Numina. Mathstral, like Isaac Newton at his time, stands on Mistral 7B's shoulders and specializes in STEM. It has the highest level of reasoning in its size category, based on industry-standard benchmarks. It achieves 56.6% in MATH and 63.47% in MMLU. The following table shows the MMLU performance differences between Mathstral and Mistral 7B.

We introduce the Granite family of decoder only code models for code generation tasks (e.g. fixing bugs, explaining codes, documenting codes), trained with code in 116 programming language. The Granite Code family has been evaluated on a variety of tasks and demonstrates that the models are consistently at the top of their game among open source code LLMs. Granite Code models have a number of key advantages. Granite Code models are able to perform at a competitive level or even at the cutting edge of technology in a variety of code-related tasks including code generation, explanations, fixing, translation, editing, and more. Demonstrating the ability to solve a variety of coding tasks. IBM's Corporate Legal team guides all models for trustworthy enterprise use. All models are trained using license-permissible datasets collected according to IBM's AI Ethics Principles.

DeepSeek is an advanced AI assistant powered by the DeepSeek-V3 model, leveraging over 600 billion parameters to deliver powerful and reliable performance. Competing with leading AI technologies, it provides quick answers and a wide array of tools to streamline daily tasks. Accessible on iOS, Android, and via the web, DeepSeek ensures convenience across devices and supports multiple languages to cater to a global audience. Regular updates enhance its functionality, resolve bugs, and introduce new language options, offering an ever-improving user experience. With its impressive capabilities, DeepSeek has earned praise for its speed, versatility, and ease of use.

A model parallel autoregressive transformator implementation on GPUs based on the DeepSpeed Library. This repository contains EleutherAI’s library for training large language models on GPUs. Our current framework is based upon NVIDIA's Megatron Language Model, and has been enhanced with techniques from DeepSpeed, as well as some novel improvements. This repo is intended to be a central and accessible place for techniques to train large-scale autoregressive models and to accelerate research into large scale training.

Tülu 3 is a cutting-edge instruction-following language model created by the Allen Institute for AI (AI2), designed to enhance reasoning, coding, mathematics, knowledge retrieval, and safety. Built on the Llama 3 Base model, Tülu 3 undergoes a four-stage post-training process that includes curated prompt synthesis, supervised fine-tuning, preference tuning with diverse datasets, and reinforcement learning to improve targeted skills with verifiable results. As an open-source model, it prioritizes transparency by providing access to training data, evaluation tools, and code, bridging the gap between open and proprietary AI fine-tuning techniques. Performance evaluations demonstrate that Tülu 3 surpasses other similarly sized open-weight models, including Llama 3.1-Instruct and Qwen2.5-Instruct, across multiple benchmarks.

Perplexity AI has introduced R1 1776 as an open-source variant of DeepSeek R1, aiming to advance transparency and collaboration in AI research. By making the model’s architecture and codebase publicly accessible, developers and researchers can refine and expand its capabilities for diverse applications. This initiative not only encourages community-driven innovation but also reinforces ethical AI development by building on the foundation of DeepSeek R1.