Alternatives to Command R

Gemini is Google’s intelligent AI platform built to support productivity, creativity, and learning across work, school, and everyday life. It allows users to ask questions, generate text, images, and videos, and explore ideas using conversational AI powered by Gemini 3. By integrating directly with Google Search, Gemini provides grounded answers and supports detailed follow-up discussions on complex topics. The platform includes advanced tools like Deep Research, which condenses hours of online research into structured reports in minutes. Gemini also enables real-time collaboration and spoken brainstorming through Gemini Live. Users can connect Gemini to Gmail, Google Docs, Calendar, Maps, and other Google services to complete tasks across multiple apps at once. Custom AI experts called Gems allow users to save instructions and tailor Gemini for specific roles or workflows. Gemini supports large file analysis with a long context window, making it capable of reviewing books, reports, and large codebases. Flexible subscription tiers offer different levels of access to models, credits, and creative tools. Gemini is available on web and mobile, making it accessible wherever users need intelligent assistance.

Cohere has introduced Command R+, its latest large language model designed to excel in conversational interactions and manage long-context tasks with remarkable efficiency. This model is tailored for organizations looking to transition from experimental phases to full-scale production. We suggest utilizing Command R+ for workflows that require advanced retrieval-augmented generation capabilities and the use of multiple tools in a sequence. Conversely, Command R is well-suited for less complicated retrieval-augmented generation tasks and scenarios involving single-step tool usage, particularly when cost-effectiveness is a key factor in decision-making.

Cohere has launched Command A, an advanced AI model engineered to enhance efficiency while using minimal computational resources. This model not only competes with but also surpasses other leading models such as GPT-4 and DeepSeek-V3 in various enterprise tasks that require agentic capabilities, all while dramatically lowering computing expenses. Command A is specifically designed for applications that demand rapid and efficient AI solutions, enabling organizations to carry out complex tasks across multiple fields without compromising on performance or computational efficiency. Its innovative architecture allows businesses to harness the power of AI effectively, streamlining operations and driving productivity.

Mistral Saba is an advanced model boasting 24 billion parameters, developed using carefully selected datasets from the Middle East and South Asia. It outperforms larger models—those more than five times its size—in delivering precise and pertinent responses, all while being notably faster and more cost-effective. Additionally, it serves as an excellent foundation for creating highly specialized regional adaptations. This model can be accessed via an API and is also capable of being deployed locally to meet customers' security requirements. Similar to the recently introduced Mistral Small 3, it is lightweight enough to operate on single-GPU systems, achieving response rates exceeding 150 tokens per second. Reflecting the deep cultural connections between the Middle East and South Asia, Mistral Saba is designed to support Arabic alongside numerous Indian languages, with a particular proficiency in South Indian languages like Tamil. This diverse linguistic capability significantly boosts its adaptability for multinational applications in these closely linked regions. Furthermore, the model’s design facilitates an easier integration into various platforms, enhancing its usability across different industries.

The Mixtral 8x22B represents our newest open model, establishing a new benchmark for both performance and efficiency in the AI sector. This sparse Mixture-of-Experts (SMoE) model activates only 39B parameters from a total of 141B, ensuring exceptional cost efficiency relative to its scale. Additionally, it demonstrates fluency in multiple languages, including English, French, Italian, German, and Spanish, while also possessing robust skills in mathematics and coding. With its native function calling capability, combined with the constrained output mode utilized on la Plateforme, it facilitates the development of applications and the modernization of technology stacks on a large scale. The model's context window can handle up to 64K tokens, enabling accurate information retrieval from extensive documents. We prioritize creating models that maximize cost efficiency for their sizes, thereby offering superior performance-to-cost ratios compared to others in the community. The Mixtral 8x22B serves as a seamless extension of our open model lineage, and its sparse activation patterns contribute to its speed, making it quicker than any comparable dense 70B model on the market. Furthermore, its innovative design positions it as a leading choice for developers seeking high-performance solutions.

Jamba stands out as the most potent and effective long context model, specifically designed for builders while catering to enterprise needs. With superior latency compared to other leading models of similar sizes, Jamba boasts a remarkable 256k context window, the longest that is openly accessible. Its innovative Mamba-Transformer MoE architecture focuses on maximizing cost-effectiveness and efficiency. Key features available out of the box include function calls, JSON mode output, document objects, and citation mode, all designed to enhance user experience. Jamba 1.5 models deliver exceptional performance throughout their extensive context window and consistently achieve high scores on various quality benchmarks. Enterprises can benefit from secure deployment options tailored to their unique requirements, allowing for seamless integration into existing systems. Jamba can be easily accessed on our robust SaaS platform, while deployment options extend to strategic partners, ensuring flexibility for users. For organizations with specialized needs, we provide dedicated management and continuous pre-training, ensuring that every client can leverage Jamba’s capabilities to the fullest. This adaptability makes Jamba a prime choice for enterprises looking for cutting-edge solutions.

Our advanced multimodal assistant is meticulously crafted with a focus on privacy, security, and operational efficiency. Yasa is trained to interpret various forms of content, including text, images, videos, and tabular data, with plans to expand to additional modalities in the future. It can assist you in brainstorming for creative projects, answering fundamental questions, or extracting valuable insights from your internal datasets. With just a few straightforward commands, you can generate, train, compress, or deploy it on your own servers. Our proprietary algorithms enable you to customize the model according to your specific data and requirements. We utilize innovative techniques that encompass retrieval, fine-tuning, self-supervised instruction tuning, and reinforcement learning to optimize our model based on your unique datasets, ensuring that it meets your operational needs effectively. In doing so, we aim to enhance user experience and deliver tailored solutions that drive productivity and innovation.

Hume AI has unveiled Octave, an innovative text-to-speech platform that utilizes advanced language model technology to deeply understand and interpret word context, allowing it to produce speech infused with the right emotions, rhythm, and cadence. Unlike conventional TTS systems that simply vocalize text, Octave mimics the performance of a human actor, delivering lines with rich expression tailored to the content being spoken. Users are empowered to create a variety of unique AI voices by submitting descriptive prompts, such as "a skeptical medieval peasant," facilitating personalized voice generation that reflects distinct character traits or situational contexts. Moreover, Octave supports the adjustment of emotional tone and speaking style through straightforward natural language commands, enabling users to request changes like "speak with more enthusiasm" or "whisper in fear" for precise output customization. This level of interactivity enhances user experience by allowing for a more engaging and immersive auditory experience.

We introduce T5, a model that transforms all natural language processing tasks into a consistent text-to-text format, ensuring that both inputs and outputs are text strings, unlike BERT-style models which are limited to providing either a class label or a segment of the input text. This innovative text-to-text approach enables us to utilize the same model architecture, loss function, and hyperparameter settings across various NLP tasks such as machine translation, document summarization, question answering, and classification, including sentiment analysis. Furthermore, T5's versatility extends to regression tasks, where it can be trained to output the textual form of a number rather than the number itself, showcasing its adaptability. This unified framework greatly simplifies the handling of diverse NLP challenges, promoting efficiency and consistency in model training and application.

Sparrow serves as a research prototype and a demonstration project aimed at enhancing the training of dialogue agents to be more effective, accurate, and safe. By instilling these attributes within a generalized dialogue framework, Sparrow improves our insights into creating agents that are not only safer but also more beneficial, with the long-term ambition of contributing to the development of safer and more effective artificial general intelligence (AGI). Currently, Sparrow is not available for public access. The task of training conversational AI presents unique challenges, particularly due to the complexities involved in defining what constitutes a successful dialogue. To tackle this issue, we utilize a method of reinforcement learning (RL) that incorporates feedback from individuals, which helps us understand their preferences regarding the usefulness of different responses. By presenting participants with various model-generated answers to identical questions, we gather their opinions on which responses they find most appealing, thus refining our training process. This feedback loop is crucial for enhancing the performance and reliability of dialogue agents.

Samsung Gauss is an innovative AI model crafted by Samsung Electronics, designed to serve as a large language model that has been trained on an extensive array of text and code. This advanced model is capable of producing coherent text, translating various languages, creating diverse forms of artistic content, and providing informative answers to a wide range of inquiries. Although Samsung Gauss is still being refined, it has already demonstrated proficiency in a variety of tasks, such as: Following directives and fulfilling requests with careful consideration. Offering thorough and insightful responses to questions, regardless of their complexity or peculiarity. Crafting different types of creative outputs, which include poems, programming code, scripts, musical compositions, emails, and letters. To illustrate its capabilities, Samsung Gauss can translate text among numerous languages, including English, French, German, Spanish, Chinese, Japanese, and Korean, while also generating functional code tailored to specific programming needs. Ultimately, as development continues, the potential applications of Samsung Gauss are bound to expand even further.

The Nova 2 Lite is an efficient and rapid reasoning model specifically crafted to manage typical AI tasks related to text, images, and video. It produces coherent and context-sensitive responses while allowing users to adjust the level of internal reasoning, known as “thinking depth,” before arriving at an answer. This versatility empowers teams to opt for quicker responses or more thorough resolutions based on their specific needs. It is particularly effective in applications such as customer service chatbots, automated documentation processes, and overall business workflow enhancement. Nova 2 Lite excels in standard evaluation tests, often matching or surpassing other similar compact models in various benchmark assessments, which highlights its dependable understanding and quality of responses. Its notable capabilities encompass analyzing intricate documents, extracting precise insights from video materials, generating functional code, and providing well-grounded answers based on the information presented. Additionally, its adaptability makes it a valuable asset for diverse industries seeking to optimize their AI-driven solutions.

XLNet introduces an innovative approach to unsupervised language representation learning by utilizing a unique generalized permutation language modeling objective. Furthermore, it leverages the Transformer-XL architecture, which proves to be highly effective in handling language tasks that require processing of extended contexts. As a result, XLNet sets new benchmarks with its state-of-the-art (SOTA) performance across multiple downstream language applications, such as question answering, natural language inference, sentiment analysis, and document ranking. This makes XLNet a significant advancement in the field of natural language processing.

Grok is an artificial intelligence inspired by the Hitchhiker’s Guide to the Galaxy, aiming to respond to a wide array of inquiries while also prompting users with thought-provoking questions. With a knack for delivering responses infused with humor and a bit of irreverence, Grok is not the right choice for those who dislike a lighthearted approach. A distinctive feature of Grok is its ability to access real-time information through the 𝕏 platform, allowing it to tackle bold and unconventional questions that many other AI systems might shy away from. This capability not only enhances its versatility but also ensures that users receive answers that are both timely and engaging.

BERT is a significant language model that utilizes a technique for pre-training language representations. This pre-training process involves initially training BERT on an extensive dataset, including resources like Wikipedia. Once this foundation is established, the model can be utilized for diverse Natural Language Processing (NLP) applications, including tasks such as question answering and sentiment analysis. Additionally, by leveraging BERT alongside AI Platform Training, it becomes possible to train various NLP models in approximately half an hour, streamlining the development process for practitioners in the field. This efficiency makes it an appealing choice for developers looking to enhance their NLP capabilities.

Upstage AI specializes in developing cutting-edge large language models and document processing tools that streamline workflows in mission-critical industries such as insurance, healthcare, and finance. Their flagship product, Solar Pro 2, offers enterprise-grade speed and reliability, optimized for handling complex language tasks with grounded, accurate outputs. Upstage’s Document Parse converts PDFs, scans, and emails into clean, machine-readable data, while Information Extract pulls structured key-value pairs from invoices, claims, and contracts with audited precision. These AI-driven solutions automate time-consuming tasks like claims adjudication, policy management, and clinical documentation review, enabling faster and more informed decision-making. The company provides flexible deployment methods, including SaaS, private cloud, and on-premises installations, ensuring data sovereignty and compliance. Upstage’s AI technology has earned recognition such as the CB Insights AI 100 listing and the top spot on the Open LLM Leaderboard. Leading companies rely on Upstage to unlock hidden insights in complex documents, saving hours of manual review. Its high accuracy OCR and GenAI capabilities continue to push the boundaries of enterprise AI.

Claude Pro is a sophisticated large language model created to tackle intricate tasks while embodying a warm and approachable attitude. With a foundation built on comprehensive, high-quality information, it shines in grasping context, discerning subtle distinctions, and generating well-organized, coherent replies across various subjects. By utilizing its strong reasoning abilities and an enhanced knowledge repository, Claude Pro is capable of crafting in-depth reports, generating creative pieces, condensing extensive texts, and even aiding in programming endeavors. Its evolving algorithms consistently enhance its capacity to absorb feedback, ensuring that the information it provides remains precise, dependable, and beneficial. Whether catering to professionals seeking specialized assistance or individuals needing quick, insightful responses, Claude Pro offers a dynamic and efficient conversational encounter, making it a valuable tool for anyone in need of information or support.

Contextual AI has unveiled its Grounded Language Model (GLM), which is meticulously crafted to reduce inaccuracies and provide highly reliable, source-based replies for retrieval-augmented generation (RAG) as well as agentic applications. This advanced model emphasizes fidelity to the information provided, ensuring that responses are firmly anchored in specific knowledge sources and are accompanied by inline citations. Achieving top-tier results on the FACTS groundedness benchmark, the GLM demonstrates superior performance compared to other foundational models in situations that demand exceptional accuracy and dependability. Tailored for enterprise applications such as customer service, finance, and engineering, the GLM plays a crucial role in delivering trustworthy and exact responses, which are essential for mitigating risks and enhancing decision-making processes. Furthermore, its design reflects a commitment to meeting the rigorous demands of industries where information integrity is paramount.

GPT-5 Thinking is a specialized reasoning component of the GPT-5 platform that activates when queries require deeper thought and complex problem-solving. Unlike the quick-response GPT-5 base model, GPT-5 Thinking carefully processes multifaceted questions, delivering richer and more precise answers. This enhanced reasoning mode excels in reducing factual errors and hallucinations by analyzing information more thoroughly and applying multi-step logic. It also improves transparency by clearly stating when certain tasks cannot be completed due to missing data or unsupported requests. Safety is a core focus, with GPT-5 Thinking trained to balance helpfulness and risk, especially in sensitive or dual-use scenarios. The model seamlessly switches between fast and deep thinking based on conversation complexity and user intent. With improved instruction following and reduced sycophancy, GPT-5 Thinking offers more natural, confident, and thoughtful interactions. It is accessible to all users as part of GPT-5’s unified system, enhancing both everyday productivity and expert applications.

DataGemma signifies a groundbreaking initiative by Google aimed at improving the precision and dependability of large language models when handling statistical information. Released as a collection of open models, DataGemma utilizes Google's Data Commons, a comprehensive source of publicly available statistical information, to root its outputs in actual data. This project introduces two cutting-edge methods: Retrieval Interleaved Generation (RIG) and Retrieval Augmented Generation (RAG). The RIG approach incorporates real-time data verification during the content generation phase to maintain factual integrity, while RAG focuses on acquiring pertinent information ahead of producing responses, thereby minimizing the risk of inaccuracies often referred to as AI hallucinations. Through these strategies, DataGemma aspires to offer users more reliable and factually accurate answers, representing a notable advancement in the effort to combat misinformation in AI-driven content. Ultimately, this initiative not only underscores Google's commitment to responsible AI but also enhances the overall user experience by fostering trust in the information provided.

The GLM-4.6V is an advanced, open-source multimodal vision-language model that belongs to the Z.ai (GLM-V) family, specifically engineered for tasks involving reasoning, perception, and action. It is available in two configurations: a comprehensive version with 106 billion parameters suitable for cloud environments or high-performance computing clusters, and a streamlined “Flash” variant featuring 9 billion parameters, which is tailored for local implementation or scenarios requiring low latency. With a remarkable native context window that accommodates up to 128,000 tokens during its training phase, GLM-4.6V can effectively manage extensive documents or multimodal data inputs. One of its standout features is the built-in Function Calling capability, allowing the model to accept various forms of visual media — such as images, screenshots, and documents — as inputs directly, eliminating the need for manual text conversion. This functionality not only facilitates reasoning about the visual content but also enables the model to initiate tool calls, effectively merging visual perception with actionable results. The versatility of GLM-4.6V opens the door to a wide array of applications, including the generation of interleaved image-and-text content, which can seamlessly integrate document comprehension with text summarization or the creation of responses that include image annotations, thereby greatly enhancing user interaction and output quality.

Cohere is a robust enterprise AI platform that empowers developers and organizations to create advanced applications leveraging language technologies. With a focus on large language models (LLMs), Cohere offers innovative solutions for tasks such as text generation, summarization, and semantic search capabilities. The platform features the Command family designed for superior performance in language tasks, alongside Aya Expanse, which supports multilingual functionalities across 23 different languages. Emphasizing security and adaptability, Cohere facilitates deployment options that span major cloud providers, private cloud infrastructures, or on-premises configurations to cater to a wide array of enterprise requirements. The company partners with influential industry players like Oracle and Salesforce, striving to weave generative AI into business applications, thus enhancing automation processes and customer interactions. Furthermore, Cohere For AI, its dedicated research lab, is committed to pushing the boundaries of machine learning via open-source initiatives and fostering a collaborative global research ecosystem. This commitment to innovation not only strengthens their technology but also contributes to the broader AI landscape.

GPT-4, or Generative Pre-trained Transformer 4, is a highly advanced unsupervised language model that is anticipated for release by OpenAI. As the successor to GPT-3, it belongs to the GPT-n series of natural language processing models and was developed using an extensive dataset comprising 45TB of text, enabling it to generate and comprehend text in a manner akin to human communication. Distinct from many conventional NLP models, GPT-4 operates without the need for additional training data tailored to specific tasks. It is capable of generating text or responding to inquiries by utilizing only the context it creates internally. Demonstrating remarkable versatility, GPT-4 can adeptly tackle a diverse array of tasks such as translation, summarization, question answering, sentiment analysis, and more, all without any dedicated task-specific training. This ability to perform such varied functions further highlights its potential impact on the field of artificial intelligence and natural language processing.

Adept is a research and product laboratory focused on developing general intelligence through the collaboration of humans and computers in a creative manner. Its design and training are tailored specifically for executing tasks on computers based on natural language instructions. The introduction of ACT-1 marks our initial venture towards creating a foundational model capable of utilizing every available software tool, API, and website. Adept is pioneering a revolutionary approach to accomplishing tasks, translating your objectives expressed in everyday language into actionable steps within the software you frequently utilize. We are committed to ensuring that AI systems prioritize user needs, allowing machines to assist people in taking charge of their work, uncovering innovative solutions, facilitating better decision-making, and freeing up more time for the activities we are passionate about. By focusing on this collaborative dynamic, Adept aims to transform how we engage with technology in our daily lives.

Use generative language models for improving and optimizing your web services and applications. Get a consolidated result of textual data, whether it is information from chats at work, user reviews or other types. YandexGPT can help summarize and interpret information. Improve the quality and style of your text to speed up the creation process. Create templates for newsletters, product description for online stores, and other applications. Create a chatbot to help your customer service. Teach the bot how to answer common and complex questions. Use the API to automate processes and integrate the service into your applications.

The GPT-5.2 Instant model represents a swift and efficient iteration within OpenAI's GPT-5.2 lineup, tailored for routine tasks and learning, showcasing notable advancements in responding to information-seeking inquiries, how-to guidance, technical documentation, and translation tasks compared to earlier models. This version builds upon the more engaging conversational style introduced in GPT-5.1 Instant, offering enhanced clarity in its explanations that prioritize essential details, thus facilitating quicker access to precise answers for users. With its enhanced speed and responsiveness, GPT-5.2 Instant is adept at performing common functions such as handling inquiries, creating summaries, supporting research efforts, and aiding in writing and editing tasks, while also integrating extensive enhancements from the broader GPT-5.2 series that improve reasoning abilities, manage longer contexts, and ensure factual accuracy. As a part of the GPT-5.2 family, it benefits from shared foundational improvements that elevate its overall reliability and performance for a diverse array of daily activities. Users can expect a more intuitive interaction experience and a significant reduction in the time spent searching for information.

OpenGPT-X is an initiative based in Germany that is dedicated to creating large AI language models specifically designed to meet the needs of Europe, highlighting attributes such as adaptability, reliability, multilingual support, and open-source accessibility. This initiative unites various partners to encompass the full spectrum of the generative AI value chain, which includes scalable, GPU-powered infrastructure and data for training expansive language models, alongside model design and practical applications through prototypes and proofs of concept. The primary goal of OpenGPT-X is to promote innovative research with a significant emphasis on business applications, thus facilitating the quicker integration of generative AI within the German economic landscape. Additionally, the project places a strong importance on the ethical development of AI, ensuring that the models developed are both reliable and consistent with European values and regulations. Furthermore, OpenGPT-X offers valuable resources such as the LLM Workbook and a comprehensive three-part reference guide filled with examples and resources to aid users in grasping the essential features of large AI language models, ultimately fostering a deeper understanding of this technology. By providing these tools, OpenGPT-X not only supports the technical development of AI but also encourages responsible usage and implementation across various sectors.

Atla's Selene 1 API delivers cutting-edge AI evaluation models, empowering developers to set personalized assessment standards and achieve precise evaluations of their AI applications' effectiveness. Selene surpasses leading models on widely recognized evaluation benchmarks, guaranteeing trustworthy and accurate assessments. Users benefit from the ability to tailor evaluations to their unique requirements via the Alignment Platform, which supports detailed analysis and customized scoring systems. This API not only offers actionable feedback along with precise evaluation scores but also integrates smoothly into current workflows. It features established metrics like relevance, correctness, helpfulness, faithfulness, logical coherence, and conciseness, designed to tackle prevalent evaluation challenges, such as identifying hallucinations in retrieval-augmented generation scenarios or contrasting results with established ground truth data. Furthermore, the flexibility of the API allows developers to innovate and refine their evaluation methods continuously, making it an invaluable tool for enhancing AI application performance.

The MiniMax‑M1 model, introduced by MiniMax AI and licensed under Apache 2.0, represents a significant advancement in hybrid-attention reasoning architecture. With an extraordinary capacity for handling a 1 million-token context window and generating outputs of up to 80,000 tokens, it facilitates in-depth analysis of lengthy texts. Utilizing a cutting-edge CISPO algorithm, MiniMax‑M1 was trained through extensive reinforcement learning, achieving completion on 512 H800 GPUs in approximately three weeks. This model sets a new benchmark in performance across various domains, including mathematics, programming, software development, tool utilization, and understanding of long contexts, either matching or surpassing the capabilities of leading models in the field. Additionally, users can choose between two distinct variants of the model, each with a thinking budget of either 40K or 80K, and access the model's weights and deployment instructions on platforms like GitHub and Hugging Face. Such features make MiniMax‑M1 a versatile tool for developers and researchers alike.

A marketplace driven by community engagement allows developers to create specialized expert LLMs focused on technical subjects, surpassing traditional AI models in performance. These Lunes significantly reduce inaccuracies in technical inquiries by continuously updating themselves with information from a variety of technical knowledge sources, including GitHub repositories and official documentation. Users can receive references akin to those provided by Perplexity, and access numerous Lunes built by other users, which range from those trained on open-source tools to well-curated collections of technology blog articles. You can also develop your own Lune by aggregating resources, including personal projects, to gain visibility. Our API seamlessly integrates with OpenAI’s, facilitating easy compatibility with tools like Cursor, Continue, and other applications that utilize OpenAI-compatible models. Conversations can effortlessly transition from your IDE to Lune Web at any point, enhancing user experience. Contributions made during chats can earn you compensation for every piece of feedback that gets approved. Alternatively, you can create a public Lune and share it widely, earning money based on its popularity and user engagement. This innovative approach not only fosters collaboration but also rewards users for their expertise and creativity.

GLM-4.5V-Flash is a vision-language model that is open source and specifically crafted to integrate robust multimodal functionalities into a compact and easily deployable framework. It accommodates various types of inputs including images, videos, documents, and graphical user interfaces, facilitating a range of tasks such as understanding scenes, parsing charts and documents, reading screens, and analyzing multiple images. In contrast to its larger counterparts, GLM-4.5V-Flash maintains a smaller footprint while still embodying essential visual language model features such as visual reasoning, video comprehension, handling GUI tasks, and parsing complex documents. This model can be utilized within “GUI agent” workflows, allowing it to interpret screenshots or desktop captures, identify icons or UI components, and assist with both automated desktop and web tasks. While it may not achieve the performance enhancements seen in the largest models, GLM-4.5V-Flash is highly adaptable for practical multimodal applications where efficiency, reduced resource requirements, and extensive modality support are key considerations. Its design ensures that users can harness powerful functionalities without sacrificing speed or accessibility.

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.

Huawei has created an AI chatbot known as PanGu Chat, which is capable of engaging in human-like conversations and providing answers to inquiries in a manner similar to ChatGPT. This technology aims to enhance user interaction by simulating natural dialogue.

Utilize sophisticated coding and language models across a diverse range of applications. Harness the power of expansive generative AI models that possess an intricate grasp of both language and code, paving the way for enhanced reasoning and comprehension skills essential for developing innovative applications. These advanced models can be applied to multiple scenarios, including writing support, automatic code creation, and data reasoning. Moreover, ensure responsible AI practices by implementing measures to detect and mitigate potential misuse, all while benefiting from enterprise-level security features offered by Azure. With access to generative models pretrained on vast datasets comprising trillions of words, you can explore new possibilities in language processing, code analysis, reasoning, inferencing, and comprehension. Further personalize these generative models by using labeled datasets tailored to your unique needs through an easy-to-use REST API. Additionally, you can optimize your model's performance by fine-tuning hyperparameters for improved output accuracy. The few-shot learning functionality allows you to provide sample inputs to the API, resulting in more pertinent and context-aware outcomes. This flexibility enhances your ability to meet specific application demands effectively.

NuExtract is an advanced tool designed for extracting structured data from various document formats, such as text files, scanned images, PDFs, PowerPoints, spreadsheets, among others, while accommodating multiple languages and mixed-language inputs. It generates output in JSON format that adheres to user-specified templates, incorporating verification and handling of null values to reduce inaccuracies. Users can initiate extraction tasks by crafting a template through either specifying the fields they want or importing existing formats; they can enhance precision by including example documents and expected outputs in the example set. The NuExtract Platform boasts a user-friendly interface for template creation, extraction testing in a sandbox environment, managing teaching examples, and adjusting parameters like model temperature and document rasterization DPI. After completion of validation, projects can be executed through a RESTful API endpoint, enabling real-time processing of documents. This seamless integration allows users to efficiently manage their data extraction needs, enhancing both productivity and accuracy in their workflows.

Innovations in healthcare have the potential to transform lives and inspire hope, driven by a combination of scientific expertise, empathy, and human understanding. We are confident that artificial intelligence can play a significant role in this transformation through effective collaboration among researchers, healthcare providers, and the wider community. Today, we are thrilled to announce promising strides in these efforts, unveiling limited access to Google’s medical-focused large language model, Med-PaLM 2. In the upcoming weeks, this model will be made available for restricted testing to a select group of Google Cloud clients, allowing them to explore its applications and provide valuable feedback as we pursue safe and responsible methods of leveraging this technology. Med-PaLM 2 utilizes Google’s advanced LLMs, specifically tailored for the medical field, to enhance the accuracy and safety of responses to medical inquiries. Notably, Med-PaLM 2 achieved the distinction of being the first LLM to perform at an “expert” level on the MedQA dataset, which consists of questions modeled after the US Medical Licensing Examination (USMLE). This milestone reflects our commitment to advancing healthcare through innovative solutions and highlights the potential of AI in addressing complex medical challenges.

Grok 4.1 Fast represents xAI’s leap forward in building highly capable agents that rely heavily on tool calling, long-context reasoning, and real-time information retrieval. It supports a robust 2-million-token window, enabling long-form planning, deep research, and multi-step workflows without degradation. Through extensive RL training and exposure to diverse tool ecosystems, the model performs exceptionally well on demanding benchmarks like τ²-bench Telecom. When paired with the Agent Tools API, it can autonomously browse the web, search X posts, execute Python code, and retrieve documents, eliminating the need for developers to manage external infrastructure. It is engineered to maintain intelligence across multi-turn conversations, making it ideal for enterprise tasks that require continuous context. Its benchmark accuracy on tool-calling and function-calling tasks clearly surpasses competing models in speed, cost, and reliability. Developers can leverage these strengths to build agents that automate customer support, perform real-time analysis, and execute complex domain-specific tasks. With its performance, low pricing, and availability on platforms like OpenRouter, Grok 4.1 Fast stands out as a production-ready solution for next-generation AI systems.

ChatGPT by OpenAI is a versatile AI conversational platform that provides assistance in writing, learning, brainstorming, code generation, and problem-solving across a wide range of topics. Available for free with optional Plus and Pro subscription plans, it supports real-time text and voice interactions on web browsers and mobile apps. Users can leverage ChatGPT to create content, summarize meetings, debug code, analyze data, and even generate images using integrated tools like DALL·E 3. The platform is accessible via desktop and mobile devices and offers personalized workflows through custom GPTs and projects. Advanced plans unlock deeper research capabilities, extended limits, and access to cutting-edge AI models like GPT-4o and OpenAI o1 pro mode. ChatGPT integrates search capabilities for real-time information and enables collaboration through features like Canvas for project editing. It caters to students, professionals, hobbyists, and developers seeking efficient, AI-driven support. OpenAI continually updates ChatGPT with new tools and enhanced usability.

Palmyra represents a collection of Large Language Models (LLMs) specifically designed to deliver accurate and reliable outcomes in business settings. These models shine in various applications, including answering questions, analyzing images, and supporting more than 30 languages, with options for fine-tuning tailored to sectors such as healthcare and finance. Remarkably, the Palmyra models have secured top positions in notable benchmarks such as Stanford HELM and PubMedQA, with Palmyra-Fin being the first to successfully clear the CFA Level III examination. Writer emphasizes data security by refraining from utilizing client data for training or model adjustments, adhering to a strict zero data retention policy. The Palmyra suite features specialized models, including Palmyra X 004, which boasts tool-calling functionalities; Palmyra Med, created specifically for the healthcare industry; Palmyra Fin, focused on financial applications; and Palmyra Vision, which delivers sophisticated image and video processing capabilities. These advanced models are accessible via Writer's comprehensive generative AI platform, which incorporates graph-based Retrieval Augmented Generation (RAG) for enhanced functionality. With continual advancements and improvements, Palmyra aims to redefine the landscape of enterprise-level AI solutions.

PanGu-α has been created using the MindSpore framework and utilizes a powerful setup of 2048 Ascend 910 AI processors for its training. The training process employs an advanced parallelism strategy that leverages MindSpore Auto-parallel, which integrates five different parallelism dimensions—data parallelism, operation-level model parallelism, pipeline model parallelism, optimizer model parallelism, and rematerialization—to effectively distribute tasks across the 2048 processors. To improve the model's generalization, we gathered 1.1TB of high-quality Chinese language data from diverse fields for pretraining. We conduct extensive tests on PanGu-α's generation capabilities across multiple situations, such as text summarization, question answering, and dialogue generation. Additionally, we examine how varying model scales influence few-shot performance across a wide array of Chinese NLP tasks. The results from our experiments highlight the exceptional performance of PanGu-α, demonstrating its strengths in handling numerous tasks even in few-shot or zero-shot contexts, thus showcasing its versatility and robustness. This comprehensive evaluation reinforces the potential applications of PanGu-α in real-world scenarios.

The Grok-3 Mini, developed by xAI, serves as a nimble and perceptive AI assistant specifically designed for individuals seeking prompt yet comprehensive responses to their inquiries. Retaining the core attributes of the Grok series, this compact variant offers a lighthearted yet insightful viewpoint on various human experiences while prioritizing efficiency. It caters to those who are constantly on the go or have limited access to resources, ensuring that the same level of inquisitiveness and support is delivered in a smaller package. Additionally, Grok-3 Mini excels at addressing a wide array of questions, offering concise insights without sacrificing depth or accuracy, which makes it an excellent resource for navigating the demands of contemporary life. Ultimately, it embodies a blend of practicality and intelligence that meets the needs of modern users.

Baidu’s ERNIE 4.5 Turbo represents the next step in multimodal AI capabilities, combining advanced reasoning with the ability to process diverse forms of media like text, images, and audio. The model’s improved logical reasoning and memory retention ensure that businesses and developers can rely on more accurate outputs, whether for content generation, enterprise solutions, or educational tools. Despite its advanced features, ERNIE 4.5 Turbo is an affordable solution, priced at just a fraction of the competition. Baidu also plans to release this model as open-source in 2025, fostering greater accessibility for developers worldwide.

PaLM 2 represents the latest evolution in large language models, continuing Google's tradition of pioneering advancements in machine learning and ethical AI practices. It demonstrates exceptional capabilities in complex reasoning activities such as coding, mathematics, classification, answering questions, translation across languages, and generating natural language, surpassing the performance of previous models, including its predecessor PaLM. This enhanced performance is attributed to its innovative construction, which combines optimal computing scalability, a refined mixture of datasets, and enhancements in model architecture. Furthermore, PaLM 2 aligns with Google's commitment to responsible AI development and deployment, having undergone extensive assessments to identify potential harms, biases, and practical applications in both research and commercial products. This model serves as a foundation for other cutting-edge applications, including Med-PaLM 2 and Sec-PaLM, while also powering advanced AI features and tools at Google, such as Bard and the PaLM API. Additionally, its versatility makes it a significant asset in various fields, showcasing the potential of AI to enhance productivity and innovation.

GPT-4.5 represents a significant advancement in AI technology, building on previous models by expanding its unsupervised learning techniques, refining its reasoning skills, and enhancing its collaborative features. This model is crafted to better comprehend human intentions and engage in more natural and intuitive interactions, resulting in greater accuracy and reduced hallucination occurrences across various subjects. Its sophisticated functions allow for the creation of imaginative and thought-provoking content, facilitate the resolution of intricate challenges, and provide support in various fields such as writing, design, and even space exploration. Furthermore, the model's enhanced ability to interact with humans paves the way for practical uses, ensuring that it is both more accessible and dependable for businesses and developers alike. By continually evolving, GPT-4.5 sets a new standard for how AI can assist in diverse applications and industries.

We have developed a model known as ChatGPT that engages users in dialogue. This conversational structure allows ChatGPT to effectively respond to follow-up inquiries, acknowledge errors, question faulty assumptions, and decline unsuitable requests. InstructGPT, a related model, focuses on adhering to specific instructions given in prompts and delivering comprehensive answers. ChatGPT Plus is a premium subscription service designed for ChatGPT, the conversational AI. The subscription costs $20 per month, offering subscribers several advantages: - Uninterrupted access to ChatGPT, even during high-demand periods - Accelerated response times - Access to GPT-4 - Integration of ChatGPT plugins - Capability for web-browsing with ChatGPT - Priority for new features and enhancements Currently, ChatGPT Plus is accessible to users in the United States, with plans to gradually invite individuals from our waitlist in the upcoming weeks. We also aim to broaden access and support to more countries and regions in the near future, ensuring that a wider audience can experience its benefits.