AI model

AI Fiesta offers multiple top AI models, allowing users to compare model answers and choose the AI ​​best suited for each task. The main advantage of this product is that it aggregates multiple top AI models, provides convenient comparison functions, is reasonably priced and has powerful functions.

Horizon Alpha is a platform integrated with next-generation artificial intelligence to provide fast, reliable solutions for modern creators. Its main advantage is to lead the development of artificial intelligence technology and provide excellent reasoning, coding and natural language understanding capabilities. This product is positioned as an enterprise-level AI platform and has excellent performance and flexibility.

Open WebUI Desktop is a cross-platform desktop application designed to simplify the installation and use of Open WebUI. The application allows users to turn their device into a powerful server, eliminating complicated manual setup. This project is currently in the alpha stage and is still under active development. It provides one-click installation and the ability to use offline, making it ideal for developers and users looking for efficiency and convenience.

Suverenum is a product designed to provide local AI solutions. It allows users to run AI models on their laptops, enabling them to handle 95% of their daily AI needs. The main advantage of Suverenum is that it can work offline and protect users' data privacy. The product is positioned to provide users with high-performance AI solutions while maintaining simplicity and ease of use.

OnSpace.AI is a leading no-code AI application building platform that allows users to go from concept to application in minutes. Its powerful features include quickly converting ideas into actual products, no coding skills required, building customized AI applications, etc.

Stakpak is an open source AI DevOps agent that helps you quickly identify root causes, optimize cloud costs, strengthen IAM security, automatically containerize applications, and provide a powerful production-ready infrastructure. It is designed to simplify operations and development workflows, supports CI/CD pipelines and cloud environments, and provides high security and intelligent adaptive recommendations.

JoyAgent-JDGenie is a general multi-agent framework that can quickly build agent products. Users only need to enter tasks or queries to get direct solutions. This product emphasizes high completion and lightweight design, has strong versatility, and performs well on the GAIA list. It is suitable for enterprises or developers who require quick response and efficient execution. This product is free and open source, and is positioned to provide convenient intelligent agent development solutions.

Tile is a powerful tool that helps users quickly build production-ready mobile apps using specially designed AI agents. Its key benefits include powerful AI capabilities, visual editing, mobile stack, and built-in tools and more. Tile is positioned as a tool to help users quickly publish high-quality mobile applications.

PrompTessor is an AI prompt analysis and optimization tool that helps users improve AI output. It provides deep insights, detailed metrics, and action optimization strategies through an intelligent analytics system.

Shipable is a platform designed to help users easily build, launch and scale AI agents and applications. It requires no coding and is suitable for teams, creators, and startups, with the ability to create smart tools, connect with apps like Slack and Notion, and deploy quickly.

Tila is a multi-agent AI platform that integrates workflow automation and multi-modal content creation, operating across text, images and videos through generative AI. Its main advantages include unlimited AI canvas, multi-agent technology and intelligent content generation. Positioned to improve work efficiency and create diverse content.

BestModelAI is an intelligent AI model selection tool that can automatically select the most suitable model from more than 100 options without requiring users to understand the complexity of the model. Its main advantages are intelligent routing to the best model, no need for professional knowledge, and easy and fast use.

PromptPilot is an intelligent solution platform focused on the optimization of large models and the realization of user task intentions. Through interactive feedback, the platform can automatically optimize multi-step, multi-modal and multi-scenario tasks, providing users with efficient intelligent solutions, suitable for corporate and individual users to improve work efficiency and task completion quality.

Capacity is a tool that leverages artificial intelligence technology to quickly create full-stack web applications. Its main advantages are saving development time and improving production efficiency. Capacity has rich background information and is positioned to provide users with simple and easy-to-use full-stack web application development solutions.

Instance is an AI website and app builder that quickly creates functional apps, games, and websites without coding. Its main advantages include being fast, easy to use, requiring no professional skills, and suitable for rapid prototyping and start-ups. Positioned to help users quickly transform ideas into actual products.

Nexty is a fully functional Next.js SaaS full-stack template that allows you to quickly build various commercial websites, whether it is a content station, a tool station or a paid website integrating AI capabilities. This template provides complete user authentication, payment, content management and AI functions, and its modular design helps developers focus on product innovation.

NoCode is a platform that requires no programming experience and allows users to describe ideas through natural language and quickly generate applications. It aims to lower the development threshold and allow more people to realize their ideas. The platform offers real-time preview and one-click deployment, making it ideal for users with non-technical backgrounds to help them turn their ideas into reality.

Scrapybara provides developers with a unified API to execute agents for any model and access low-level controls such as the browser, file system, and code sandbox. It handles automatic scaling, authentication, and system environments, enabling anyone to deploy agent fleets into production and automate any free-form computing task at scale.

Tokenomy is an advanced AI token calculator and cost estimating tool for LLMs. Optimize your AI prompts, analyze token usage, and save on LLM APIs like OpenAI, Anthropic, and more with Tokenomy's advanced token management tools.

Screenify is a tool that fully automatically screens and evaluates applicants through intelligent AI interviews. It helps companies screen applicants, conduct in-depth candidate assessments, and streamline the recruiting and hiring process through AI-powered interviews that resemble conversations with real people.

TaoPrompt is a professional AI prompt generation tool that can quickly and accurately create AI prompts to help users optimize the interactive experience with AI models such as ChatGPT, Claude, and Gemini. It can help users save time, improve work efficiency, and is suitable for needs in various fields.

Dump.ai is a marketplace where experts turn their expertise into AI agents and earn income. It enables experts to build, automate and earn AI agents.

BrowseWiz is a highly customizable browser extension that provides access to a wide range of AI models. It's designed to enhance your professional workflow by helping you build and leverage custom AI tools within the browser. Its main advantage is the ability to customize prompts, instructions, and even build intelligent workflows that integrate external services to achieve complex automation.

Butouzi is an AI agent development platform that integrates rich capabilities such as plug-ins, long-term and short-term memory, workflow, etc., and is designed to help users quickly build and release agents with commercial value. Its openness and flexibility enable users from all industries to find suitable solutions that suit the different needs of individuals and enterprises.

MCPify.ai is a powerful online platform that allows users to build their own MCP servers in a short time, with absolutely no programming knowledge required. Users can turn their ideas into efficient AI tools through a simple interface, suitable for multiple platforms such as Claude and Cursor. The biggest advantage of this product is its ease of use and rapid deployment, helping individuals and businesses improve work efficiency and productivity.

OpenAI's built-in tools are a collection of features in the OpenAI platform that enhance model capabilities. These tools allow models to access additional context and information in the network or files when generating responses. For example, by enabling web search tools, models can use the latest information on the web to generate responses. The main advantage of these tools is the ability to extend the model to handle more complex tasks and requirements. The OpenAI platform provides a variety of tools, such as network search, file search, computer usage, and function calls. The use of these tools depends on the prompts provided, and the model automatically decides whether to use the configured tools based on the prompts. In addition, users can explicitly control or direct the model's behavior by setting tool selection parameters. These tools are useful for scenarios that require real-time data or specific file content, making the model more useful and flexible.

OpenAI Agents SDK is a development toolkit for building autonomous agents. It builds on OpenAI's advanced model capabilities, such as advanced reasoning, multi-modal interaction, and new security technologies, to provide developers with a simplified way to build, deploy, and scale reliable agent applications. The toolkit not only supports the orchestration of single-agent and multi-agent workflows, but also integrates observability tools to help developers track and optimize the execution process of agents. Its main advantages include easy-to-configure LLM models, intelligent agent handover mechanisms, configurable safety checks, and powerful debugging and performance optimization capabilities. This toolkit is suitable for businesses and developers who need to automate complex tasks and is designed to improve productivity and efficiency through agent technology.

Steiner is a family of inference models developed by Yichao 'Peak' Ji that focus on training on synthetic data through reinforcement learning, with the ability to explore multiple paths and autonomously verify or backtrack during inference. The goal of this model is to reproduce the inference capabilities of OpenAI o1 and verify the expansion curve during inference. Steiner-preview is an ongoing project, its open source purpose is to share knowledge and get more feedback from real users. While the model performs well on some benchmarks, OpenAI o1's inference scaling capabilities have not yet been fully realized and so is still in the development stage.

Inception Labs is a company focused on developing diffusion large language models (dLLMs). Its technology is inspired by advanced image and video generation systems such as Midjourney and Sora. With diffusion models, Inception Labs offers 5-10 times faster speeds, greater efficiency, and greater control over generation than traditional autoregressive models. Its model supports parallel text generation, is able to correct errors and illusions, is suitable for multi-modal tasks, and performs well in inference and structured data generation. The company, comprised of researchers and engineers from Stanford, UCLA and Cornell University, is a pioneer in the field of diffusion modeling.

Framework Desktop is a revolutionary mini desktop designed for high-performance computing, AI model running, and gaming. It is powered by AMD Ryzen™ AI Max 300 series processors for powerful multitasking and graphics performance. The product is small in size (only 4.5L) and supports standard PC parts, allowing users to easily DIY assembly and upgrades. Designed with a focus on sustainability, using recycled materials and supporting multiple operating systems such as Linux, it is suitable for users who pursue high performance and environmental protection.

QwQ-32B is a reasoning model of the Qwen series, focusing on the thinking and reasoning capabilities of complex problems. It excels in downstream tasks, especially in solving puzzles. The model is based on the Qwen2.5 architecture and is pre-trained and optimized by reinforcement learning. It has 32.5 billion parameters and supports a processing capacity of 131,072 full context lengths. Its key benefits include powerful reasoning capabilities, efficient long text processing capabilities, and flexible deployment options. This model is suitable for scenarios that require deep thinking and complex reasoning, such as academic research, programming assistance, and creative writing.

Llasa is a text-to-speech (TTS) basic model based on the Llama framework, specially designed for large-scale speech synthesis tasks. The model is trained using 160,000 hours of labeled speech data and has efficient language generation capabilities and multi-language support. Its main advantages include powerful speech synthesis capabilities, low inference cost, and flexible framework compatibility. This model is suitable for education, entertainment and business scenarios and can provide users with high-quality speech synthesis solutions. The model is currently available for free on Hugging Face, aiming to promote the development and application of speech synthesis technology.

LLaDA is a new type of diffusion model that generates text through the diffusion process, which is different from the traditional autoregressive model. It excels in language generation scalability, instruction following, contextual learning, conversational capabilities, and compression capabilities. Developed by researchers from Renmin University of China and Ant Group, the model is 8B in size and trained entirely from scratch. Its main advantage is that it can flexibly generate text through the diffusion process and support multiple language tasks, such as mathematical problem solving, code generation, translation and multi-turn dialogue. The emergence of LLaDA provides a new direction for the development of language models, especially in terms of generation quality and flexibility.

Aria Gen 2 is the second generation of research-grade smart glasses from Meta, designed for machine perception, contextual AI and robotics research. It integrates advanced sensors and low-power machine perception technology, and can handle SLAM, eye tracking, gesture recognition and other functions in real time. This product is designed to advance the development of artificial intelligence and machine perception technology, providing researchers with powerful tools to explore how to make AI better understand the world from a human perspective. Aria Gen 2 not only achieves technological breakthroughs, it also promotes open research and public understanding of these critical technologies through collaboration with academia and commercial research laboratories.

Prompt Optimizer is a tool focused on improving the quality of AI prompt words. It uses intelligent optimization technology to help users generate more accurate and efficient prompt words, thereby improving the output quality of the AI ​​model. It supports a variety of mainstream AI models, such as OpenAI, Gemini, etc., and provides two usage methods: web application and Chrome plug-in, which are convenient for users to use in different scenarios. The tool uses a pure client-side processing architecture to ensure user data security and supports local encrypted storage of history and API keys. Its simple and intuitive interface design and smooth interactive effects provide users with a good experience.

Basalt is a platform focused on helping teams quickly move AI capabilities from ideas to real products. It simplifies the development process of AI features by providing a code-free development environment, intelligent prompts, version management and other features. The platform emphasizes collaboration, security, and best practices and is designed to address common reliability issues with AI in production environments. Basalt offers a free trial and is targeted at teams that need to quickly iterate and deploy AI capabilities.

GPT-4.5 is the latest language model released by OpenAI, which represents the current cutting-edge level of unsupervised learning technology. Through large-scale computing and data training, this model improves the understanding of world knowledge and pattern recognition capabilities, reduces hallucinations, and can interact with humans more naturally. It excels at tasks such as writing, programming, and problem-solving, and is especially suitable for scenarios that require high creativity and emotional understanding. GPT-4.5 is currently in the research preview stage and is open to Pro users and developers to explore its potential capabilities.

Poe Apps is an innovative feature launched by the Poe platform, allowing users to build visual applications based on Poe. It combines a variety of leading AI models such as text, image, video and audio generation models, operating through a simple interface or custom JavaScript logic. Poe Apps can not only run in parallel with the chat interface, but can also exist completely in a visual form, providing users with a more intuitive operating experience. Key benefits include the ability to create apps without writing code, seamless integration with the Poe platform, and leveraging users’ existing points system to avoid high API fees. The launch of Poe Apps aims to meet users' needs for AI tools in different scenarios, providing strong support for both personal creation and commercial applications.

Gemini 2.0 Flash-Lite is an efficient language model launched by Google, optimized for long text processing and complex tasks. It performs well on inference, multimodal, mathematical, and factual benchmarks, and has a simplified pricing strategy that makes million-level context windows more affordable. Gemini 2.0 Flash-Lite is fully open in Google AI Studio and Vertex AI, and is suitable for enterprise-level production use.

Phi-4-multimodal-instruct is a multimodal basic model developed by Microsoft that supports text, image and audio input and generates text output. The model is built based on the research and data sets of Phi-3.5 and Phi-4.0, and undergoes processes such as supervised fine-tuning, direct preference optimization, and human feedback reinforcement learning to improve instruction compliance and safety. It supports text, image and audio input in multiple languages, has a context length of 128K, and is suitable for a variety of multi-modal tasks, such as speech recognition, speech translation, visual question answering, etc. The model has achieved significant improvements in multi-modal capabilities, especially on speech and visual tasks. It provides developers with powerful multi-modal processing capabilities that can be used to build various multi-modal applications.

Helix is ​​an innovative vision-speech-action model designed for universal control of humanoid robots. It solves several long-term challenges for robots in complex environments by combining visual perception, language understanding and motion control. The main advantages of Helix include strong generalization capabilities, efficient data utilization, and a single neural network architecture that does not require task-specific fine-tuning. The model aims to provide robots in home environments with on-the-fly behavior generation capabilities, allowing them to handle never-before-seen items. The emergence of Helix marks an important step in adapting robotics technology to daily life scenarios.

DeepSeek is an advanced language model developed by China AI Lab supported by the High-Flyer Fund, focusing on open source models and innovative training methods. Its R1 series of models excel in logical reasoning and problem solving, using reinforcement learning and a hybrid expert framework to optimize performance and achieve efficient training at low cost. DeepSeek’s open source strategy drives community innovation while igniting industry discussions about AI competition and the impact of open source models. Its free and registration-free usage further lowers the user threshold and is suitable for a wide range of application scenarios.

QwQ-Max-Preview is the latest achievement of the Qwen series, built on Qwen2.5-Max. It shows stronger capabilities in mathematics, programming, and general tasks, and also performs well in Agent-related workflows. As a preview version of the upcoming QwQ-Max, this version is still being optimized. Its main advantages include strong capabilities for deep reasoning, mathematics, programming and agent tasks. In the future, we plan to release QwQ-Max and Qwen2.5-Max as open source under the Apache 2.0 license agreement, aiming to promote innovation in cross-domain applications.

Claude 3.7 Sonnet is the latest hybrid inference model launched by Anthropic, which can achieve seamless switching between fast response and deep inference. It excels in areas such as programming, front-end development, and provides granular control over the depth of inference via APIs. This model not only improves code generation and debugging capabilities, but also optimizes the processing of complex tasks, making it suitable for enterprise-level applications. Pricing is consistent with its predecessor, charging $3 per million tokens for input and $15 per million tokens for output.

Fiverr Go is an innovative tool launched by Fiverr that aims to increase the productivity and creativity of freelancers through AI technology. It allows freelancers to train and manage personalized AI models to generate content that matches their unique style, such as images, copy, and audio. This technology not only increases creative efficiency but also ensures freelancers have creative ownership of their work. The emergence of Fiverr Go meets the market demand for fast, high-quality content, while providing new business opportunities and income sources for freelancers. Aimed primarily at Level 2 and above freelancers, AI Creation Models is priced at $25 per month and includes 3 active models and 2 retrainings per month.

AlphaMaze is a decoder language model designed specifically to solve visual reasoning tasks. It demonstrates the potential of language models for visual reasoning by training them on a maze-solving task. The model is built on the 1.5 billion parameter Qwen model and trained through supervised fine-tuning (SFT) and reinforcement learning (RL). Its main advantage is that it can convert visual tasks into text format for reasoning, thus making up for the shortcomings of traditional language models in spatial understanding. The model was developed to improve AI performance on vision tasks, especially in scenarios that require step-by-step reasoning. Currently, AlphaMaze is a research project and its commercial pricing and market positioning have not yet been clarified.

Smithery is a platform based on the Model Context Protocol that allows users to extend the functionality of language models by connecting to various servers. It provides users with a flexible toolset that can dynamically enhance the capabilities of language models based on needs to better complete various tasks. The core advantage of this platform is its modularity and scalability, and users can choose the appropriate server for integration according to their needs.

Moonlight-16B-A3B is a large-scale language model developed by Moonshot AI and trained with the advanced Muon optimizer. This model significantly improves language generation capabilities by optimizing training efficiency and performance. Its main advantages include efficient optimizer design, fewer training FLOPs, and excellent performance. This model is suitable for scenarios that require efficient language generation, such as natural language processing, code generation, and multilingual dialogue. Its open source implementation and pre-trained models provide powerful tools for researchers and developers.

Moonlight is a 16B parameter mixed expert model (MoE) trained on the Muon optimizer, which performs well in large-scale training. It significantly improves training efficiency and stability by adding weight decay and adjusting parameter update ratios. The model outperforms existing models on multiple benchmarks while significantly reducing the amount of computation required for training. Moonlight's open source implementation and pre-trained models provide researchers and developers with powerful tools to support a variety of natural language processing tasks, such as text generation, code generation, and more.

Webdraw is an innovative AI application generation platform that allows users to create and use a variety of AI applications without complex programming knowledge. The platform provides a variety of functions from image generation, video production to chat assistants to meet the needs of different users. Its core advantages are that it is easy to use, feature-rich and completely free, making it suitable for individual creators, developers and enterprise users. Through Webdraw, users can quickly build and deploy AI applications to accelerate creative realization and business process automation.

Tbox is a large-model technology product based on Alipay's life scenarios. It is designed to quickly build professional-level intelligence for enterprises and help business growth. It integrates advanced technologies such as Ant Bailing Large Model, Ant Tianjian, and Lingjing Digital Human, and can realize functions such as experience upgrades and intelligent decision-making. Tbox is suitable for a variety of industries, such as people's livelihood, government affairs, travel, scenic spots, medical care, etc., and improves user experience and business efficiency through intelligent services. Its price and specific positioning vary according to the needs of the enterprise, providing customized solutions for enterprises.

AI co-scientist is a multi-agent AI system developed by the Google research team, aiming to assist scientific research through artificial intelligence technology. The system is built on Gemini 2.0 and can simulate the reasoning process of scientific methods and generate new research hypotheses and experimental plans. It uses multi-agent collaboration and uses multiple mechanisms such as generation, reflection, ranking, and evolution to continuously optimize the output results. The main advantages of AI co-scientists include efficient generation of novel scientific hypotheses, strong interdisciplinary knowledge integration capabilities, and the ability to collaborate with scientists. The system is currently in the research stage, and its application potential in biomedicine and other fields is being verified through cooperation with the world's top scientific research institutions.

HOMIE is an innovative humanoid robot teleoperation solution designed to achieve precise walking and operating tasks through reinforcement learning and low-cost exoskeleton hardware systems. The importance of this technology is that it solves the inefficiency and instability problems of traditional teleoperation systems, and enables robots to perform complex tasks more naturally through human motion capture and reinforcement learning training frameworks. Its main advantages include efficient task completion capabilities, no need for complex motion capture equipment, and fast training times. This product is mainly aimed at robotics research institutions, manufacturing and logistics industries. The price has not been clearly disclosed, but its hardware system cost is low and it has a high cost performance.

PaliGemma 2 mix is ​​an upgraded version of the visual language model launched by Google and belongs to the Gemma family. It can handle a variety of visual and language tasks, such as image segmentation, video subtitle generation, scientific question answering, etc. The model provides pre-trained checkpoints of different sizes (3B, 10B, and 28B parameters) and can be easily fine-tuned to suit a variety of visual language tasks. Its main advantages are versatility, high performance and developer-friendliness, supporting multiple frameworks (such as Hugging Face Transformers, Keras, PyTorch, etc.). This model is suitable for developers and researchers who need to efficiently handle visual and language tasks, and can significantly improve development efficiency.

BioEmu is a deep learning model developed by Microsoft for simulating the equilibrium ensemble of proteins. This technology can efficiently generate structural samples of proteins through generative deep learning methods, helping researchers better understand the dynamic behavior and structural diversity of proteins. The main advantage of this model is its scalability and efficiency, allowing it to handle complex biomolecular systems. It is suitable for research in areas such as biochemistry, structural biology and drug design, providing scientists with a powerful tool to explore the dynamic properties of proteins.

Vectara is an enterprise-oriented AI platform focused on helping enterprises quickly deploy and manage generative AI applications. It ensures the accuracy and security of AI applications by providing advanced Retrieval Augmented Generation (RAG) technology. The platform supports multi-language data processing, has high performance and scalability, and is suitable for multiple vertical industries such as finance, education, and law. Its main advantage is strong data security and privacy protection, complying with compliance standards such as SOC 2, HIPAA and GDPR. The product is positioned for the mid-to-high-end enterprise market. Although the specific price is not disclosed, a free trial option is provided.

Magma is a multi-modal basic model launched by the Microsoft research team, aiming to achieve the planning and execution of complex tasks through the combination of vision, language and movement. Through large-scale visual language data pre-training, it has the capabilities of language understanding, spatial intelligence and action planning, and can perform well in tasks such as UI navigation and robot operation. The emergence of this model provides a powerful basic framework for multi-modal AI agent tasks and has broad application prospects.

kimi-latest is the latest AI model launched by Dark Side of the Moon. It is upgraded simultaneously with Kimi smart assistant. It has powerful context processing capabilities and automatic caching capabilities, which can effectively reduce usage costs. The model supports image understanding and multiple functions such as ToolCalls and network search, making it suitable for building AI intelligent assistants or customer service systems. Its price is 1 yuan per million Tokens and is positioned as an efficient and flexible AI model solution.

Grok 3 is the latest flagship AI model developed by Elon Musk’s AI company xAI. It has significantly improved computing power and data set size, can handle complex mathematical and scientific problems, and supports multi-modal input. Its main advantage is its powerful inference capabilities, the ability to provide more accurate answers, and surpassing existing top models in some benchmarks. The launch of Grok 3 marks the further development of xAI in the field of AI, aiming to provide users with smarter and more efficient AI services. This model currently mainly provides services through Grok APP and X platform, and will also launch voice mode and enterprise API interface in the future. It is positioned as a high-end AI solution, mainly for users who require deep reasoning and multi-modal interaction.

Mistral Saba is the first customized language model launched by Mistral AI specifically for the Middle East and South Asia. With 24 billion parameters and trained on carefully curated datasets, the model delivers more accurate, relevant and lower-cost responses than comparable large models. It supports Arabic and multiple languages ​​of Indian origin, and is especially good at South Indian languages ​​(such as Tamil). It is suitable for scenarios that require precise language understanding and cultural background support. Mistral Saba can be used via API or deployed locally. It is lightweight, single-GPU system deployment and fast response, suitable for enterprise-level applications.

s1 is an inference model that focuses on achieving efficient text generation capabilities with a small number of samples. It scales at test time through budget forcing technology and is able to match the performance of o1-preview. The model was developed by Niklas Muennighoff and others, and related research was published on arXiv. The model uses Safetensors technology, has 32.8 billion parameters, and supports text generation tasks. Its main advantage is the ability to achieve high-quality inference with a small number of samples, making it suitable for scenarios that require efficient text generation.

EasyWeb is an AI-based open platform focused on building and deploying intelligent agents that can interact with browsers. It provides a simple and easy-to-use interface that allows users to quickly deploy AI agents to complete various browser-related tasks, such as travel planning, online shopping, and news gathering. The platform is based on the OpenHands architecture, supports parallel processing of multiple user requests, and allows users to switch different agents and LLMs (Large Language Models) as needed. Its main advantages include simple deployment, easy use, support for multiple task types, and completely open source, suitable for developers and researchers for secondary development and research. The emergence of EasyWeb provides new possibilities for the application of AI in automated tasks, and also provides strong support for research and development in related fields.

Qwen2.5-1M is an open source artificial intelligence language model designed for processing long sequence tasks and supports a context length of up to 1 million Tokens. This model significantly improves the performance and efficiency of long sequence processing through innovative training methods and technical optimization. It performs well on long context tasks while maintaining performance on short text tasks, making it an excellent open source alternative to existing long context models. This model is suitable for scenarios that require processing large amounts of text data, such as document analysis, information retrieval, etc., and can provide developers with powerful language processing capabilities.

Qwen2.5-Max is a large-scale Mixture-of-Expert (MoE) model that is pre-trained with more than 20 trillion tokens and post-trained with supervised fine-tuning and human feedback reinforcement learning. It performs well on multiple benchmarks, demonstrating strong knowledge and coding abilities. This model provides API interfaces through Alibaba Cloud to support developers in using it in various application scenarios. Its main advantages include powerful performance, flexible deployment methods and efficient training technology, aiming to provide smarter solutions in the field of artificial intelligence.

Gemini 2.0 is Google’s important progress in the field of generative AI and represents the latest artificial intelligence technology. It provides developers with efficient and flexible solutions through its powerful language generation capabilities, suitable for a variety of complex scenarios. Key benefits of Gemini 2.0 include high performance, low latency and a simplified pricing strategy designed to reduce development costs and increase productivity. The model is provided through Google AI Studio and Vertex AI, supports multiple modal inputs, and has a wide range of application prospects.

Gemini Pro is one of the most advanced AI models launched by Google DeepMind, designed for complex tasks and programming scenarios. It excels at code generation, complex instruction understanding, and multi-modal interaction, supporting text, image, video, and audio input. Gemini Pro provides powerful tool calling capabilities, such as Google search and code execution, and can handle up to 2 million words of contextual information, making it suitable for professional users and developers who require high-performance AI support.

OpenAI o3-mini is the latest inference model launched by OpenAI, optimized for the fields of science, technology, engineering and mathematics (STEM). It provides powerful reasoning capabilities while maintaining low cost and low latency, especially in mathematics, science and programming. The model supports a variety of developer functions, such as function calls, structured output, etc., and different inference intensities can be selected according to needs. The launch of o3-mini further reduces the cost of using inference models, making them more suitable for a wide range of application scenarios.

Mistral Small 3 is an open source language model launched by Mistral AI with 24B parameters and is licensed under the Apache 2.0 license. The model is designed for low latency and efficient performance, making it suitable for generative AI tasks that require fast responses. It achieves 81% accuracy on the Multi-Task Language Understanding (MMLU) benchmark and is able to generate text at 150 tokens per second. Mistral Small 3 is designed to provide a powerful base model for on-premises deployment and custom development to support applications in a variety of industries, such as financial services, healthcare, and robotics. This model was not trained using reinforcement learning (RL) or synthetic data, so it is early in the model production pipeline and suitable for building inference capabilities.

huggingface/open-r1 is an open source project dedicated to replicating the DeepSeek-R1 model. The project provides a series of scripts and tools for training, evaluation, and generation of synthetic data, supporting a variety of training methods and hardware configurations. Its main advantage is that it is completely open, allowing developers to use and improve it freely. It is a very valuable resource for users who want to conduct research and development in the fields of deep learning and natural language processing. The project currently has no clear pricing and is suitable for academic research and commercial use.

MNN Large Model Android App is an Android application developed by Alibaba based on large language model (LLM). It supports multiple modal inputs and outputs, including text generation, image recognition, audio transcription, and more. The application optimizes inference performance to ensure efficient operation on mobile devices while protecting user data privacy, with all processing done locally. It supports a variety of leading model providers, such as Qwen, Gemma, Llama, etc., and is suitable for a variety of scenarios.

Kokoro TTS is an AI model that focuses on text-to-speech. Its main function is to convert text content into natural and smooth speech output. This model is based on the StyleTTS 2 architecture and has 82 million parameters, which can provide efficient performance and low resource consumption while maintaining high-quality speech synthesis. Its multi-language support and customizable voice packages enable it to meet the needs of different users in a variety of scenarios, such as producing audiobooks, podcasts, training videos, etc. It is especially suitable for the education field to help improve the accessibility and attractiveness of content. In addition, Kokoro TTS is open source and free for users to use, which makes it significantly cost-effective.

Baichuan-M1-14B is an open source large language model developed by Baichuan Intelligence, specially optimized for medical scenarios. It is trained based on high-quality medical and general data of 20 trillion tokens, covering more than 20 medical departments, and has strong context understanding and long sequence task performance capabilities. The model performs well in the medical field and achieves the same results as a model of the same size in general tasks. Its innovative model structure and training methods enable it to perform well in complex tasks such as medical reasoning and disease judgment, providing strong support for artificial intelligence applications in the medical field.

UI-TARS is a next-generation native GUI agent model developed by ByteDance's research team, designed to seamlessly interact with graphical user interfaces through human-like perception, reasoning, and action capabilities. The model integrates all key components such as perception, reasoning, localization and memory, enabling end-to-end task automation without the need for predefined workflows or manual rules. Its main advantages include powerful multi-modal interaction capabilities, high-precision visual perception and semantic understanding capabilities, and excellent performance in a variety of complex task scenarios. This model is suitable for scenarios that require automated GUI interaction, such as automated testing, smart office, etc., and can significantly improve work efficiency.

UI-TARS is a new GUI agent model developed by ByteDance that focuses on seamless interaction with graphical user interfaces through human-like perception, reasoning, and action capabilities. The model integrates key components such as perception, reasoning, localization, and memory into a single visual language model, enabling end-to-end task automation without the need for predefined workflows or manual rules. Its main advantages include powerful cross-platform interaction capabilities, multi-step task execution capabilities, and the ability to learn from synthetic and real data, making it suitable for a variety of automation scenarios, such as desktop, mobile, and web environments.

Doubao-1.5-pro is a high-performance sparse MoE (Mixture of Experts) large language model developed by the Doubao team. This model achieves the ultimate balance between model performance and inference performance through integrated training-inference design. It performs well on multiple public evaluation benchmarks, especially in reasoning efficiency and multi-modal capabilities. This model is suitable for scenarios that require efficient reasoning and multi-modal interaction, such as natural language processing, image recognition, and voice interaction. Its technical background is based on the sparse activation MoE architecture, which achieves higher performance leverage than traditional dense models by optimizing the activation parameter ratio and training algorithm. In addition, the model also supports dynamic adjustment of parameters to adapt to different application scenarios and cost requirements.

Upsonic AI is a developer-oriented platform focused on building artificial intelligence agents in vertical fields. It simplifies the process of building AI-driven workflows by providing cross-platform compatibility and seamless integration. With tools like MCP (Multiple Computer Program), Upsonic AI makes advanced AI capabilities easily accessible and customizable. The product is designed to optimize costs and automate complex tasks by efficiently managing API calls. It is suitable for enterprises and developers who need efficient, scalable and customized AI solutions.

DeepSeek-R1-Distill-Llama-8B is a high-performance language model developed by the DeepSeek team, based on the Llama architecture and optimized for reinforcement learning and distillation. The model performs well in reasoning, code generation, and multilingual tasks, and is the first model in the open source community to improve reasoning capabilities through pure reinforcement learning. It supports commercial use, allows modifications and derivative works, and is suitable for academic research and corporate applications.

The Stargate project is a collaboration between OpenAI and multiple technology giants to build new AI infrastructure to support U.S. leadership in the field of AI. The project plans to invest US$500 billion over the next four years, with an initial investment of US$100 billion. By cooperating with companies such as SoftBank, Oracle, and NVIDIA, the Stargate project will promote the development of AI technology, create a large number of job opportunities, and bring huge economic benefits to the world. This program will not only support the reindustrialization of the United States, but will also provide the United States and its allies with strategic capabilities to protect national security.

MatterGen is a generative AI tool launched by Microsoft Research for material design. It can directly generate new materials with specific chemical, mechanical, electronic or magnetic properties according to the design requirements of the application, providing a new paradigm for materials exploration. The emergence of this tool is expected to accelerate the research and development process of new materials, reduce research and development costs, and play an important role in batteries, solar cells, CO2 adsorbents and other fields. Currently, MatterGen’s source code is open source on GitHub for public use and further development.

InternVL2.5-MPO is a series of multi-modal large-scale language models based on InternVL2.5 and Mixed Preference Optimization (MPO). It performs well on multi-modal tasks by integrating the newly incrementally pretrained InternViT with multiple pretrained large language models (LLMs), such as InternLM 2.5 and Qwen 2.5, using randomly initialized MLP projectors. This model series was trained on the multi-modal reasoning preference data set MMPR, which contains approximately 3 million samples. Through effective data construction processes and hybrid preference optimization technology, the model's reasoning capabilities and answer quality are improved.

MiniMax-Text-01 is a large language model developed by MiniMaxAI with 456 billion total parameters, of which 45.9 billion parameters are activated by each token. It adopts a hybrid architecture that combines Lightning Attention, Softmax Attention, and Mix of Experts (MoE) technologies, and extends the training context length to 1 million tokens through advanced parallel strategies and innovative computing-communication overlapping methods, such as Linear Attention Sequence Parallelism Plus (LASP+), Variable Length Ring Attention, Expert Tensor Parallelism (ETP), etc., and can handle contexts up to 4 million tokens during inference. In multiple academic benchmark tests, MiniMax-Text-01 demonstrated the performance of top models.

TIXAE AGENTS.ai is an agent-focused platform designed to simplify the creation, deployment and scaling of speech and text AI agents. It provides a range of out-of-the-box tools and integrations such as Voiceflow and VAPI to support dynamic agent development. Key benefits of the platform include an easy-to-use interface, powerful integration capabilities, and flexible customization options. It is mainly aimed at developers and enterprises, offers a free trial, and has various pricing plans to meet the needs of different users.

Humiris AI provides advanced AI infrastructure to help users build various applications. Its main advantages include high accuracy, high speed, low cost, and flexible deployment options. The product is aimed at enterprises and developers who need efficient AI solutions, and provides SaaS environment access or self-deployment options to meet the needs of different industries. At present, the official website does not clearly indicate the specific price, so you need to contact us to obtain a detailed quotation.

Fenado AI is a powerful productivity tool that uses artificial intelligence technology to allow users to quickly transform ideas into actual applications and websites. Its main advantage is that it can greatly shorten the development cycle and lower the technical threshold, allowing non-technical personnel to easily create their own digital products. The product positioning provides start-ups and individual developers with rapid prototyping and product launch solutions. The price is divided into $20 per month for the Prototype plan and $200 per month for the Business plan.

TimesFM is a pre-trained time series prediction model developed by Google Research for time series prediction tasks. The model is pre-trained on multiple datasets and is able to handle time series data of different frequencies and lengths. Its main advantages include high performance, high scalability, and ease of use. This model is suitable for various application scenarios that require accurate prediction of time series data, such as finance, meteorology, energy and other fields. The model is available for free on the Hugging Face platform, and users can easily download and use it.

Sonus-1 is a series of large language models (LLMs) launched by Sonus AI to push the boundaries of artificial intelligence. Designed for their high performance and multi-application versatility, these models include Sonus-1 Mini, Sonus-1 Air, Sonus-1 Pro and Sonus-1 Pro (w/ Reasoning) in different versions to suit different needs. Sonus-1 Pro (w/ Reasoning) performed well on multiple benchmarks, particularly on reasoning and math problems, demonstrating its ability to outperform other proprietary models. Sonus AI is committed to developing high-performance, affordable, reliable, and privacy-focused large-scale language models.

GLM-Zero-Preview is Zhipu's first reasoning model trained based on extended reinforcement learning technology. It focuses on enhancing AI reasoning capabilities and is good at handling mathematical logic, code and complex problems that require deep reasoning. Compared with the base model, the expert task capabilities are greatly improved without significantly reducing the general task capabilities. In AIME 2024, MATH500 and LiveCodeBench evaluations, the effect is equivalent to OpenAI o1-preview. Product background information shows that Zhipu Huazhang Technology Co., Ltd. is committed to improving the deep reasoning capabilities of the model through reinforcement learning technology. In the future, it will launch the official version of GLM-Zero to expand the deep thinking capabilities to more technical fields.

EXAONE-3.5-32B-Instruct-AWQ is a series of instruction-tuned bilingual (English and Korean) generation models developed by LG AI Research, with parameters ranging from 2.4B to 32B. These models support long context processing up to 32K tokens, demonstrating state-of-the-art performance in real-world use cases and long context understanding, while remaining competitive in the general domain compared to recently released models of similar size. This model uses AWQ quantification technology to achieve weight quantization at the 4-bit group level, optimizing the deployment efficiency of the model.

Aria-UI is a large-scale multimodal model designed for visual localization of GUI instructions. It adopts a pure visual method and does not rely on auxiliary input. It can adapt to diverse planning instructions and adapt to different tasks by synthesizing diverse and high-quality instruction samples. Aria-UI achieved new top records in both offline and online agent benchmarks, outperforming both vision-only and AXTree-dependent baselines.

vision-parse is a tool that uses visual language models (Vision LLMs) to parse PDF documents into well-formatted Markdown content. It supports multiple models, including OpenAI, LLama, and Gemini, and can intelligently identify and extract text and tables, while maintaining the document's hierarchical structure, style, and indentation. Key benefits of this tool include high-precision content extraction, format preservation, support for multiple models, and local model hosting for users who require efficient document processing.

Valley-Eagle-7B is a multi-modal large-scale model developed by Bytedance and is designed to handle a variety of tasks involving text, image and video data. The model achieved best results in internal e-commerce and short video benchmarks, and demonstrated superior performance compared to models of the same size in OpenCompass tests. Valley-Eagle-7B combines LargeMLP and ConvAdapter to build the projector, and introduces VisionEncoder to enhance the model's performance in extreme scenes.

DeepSeek-V3 is a powerful Mixture-of-Experts (MoE) language model with a total parameter volume of 671B and 37B parameters activated each time. It adopts Multi-head Latent Attention (MLA) and DeepSeekMoE architectures, which are fully verified in DeepSeek-V2. In addition, DeepSeek-V3 adopts a load balancing strategy without auxiliary loss for the first time and sets a multi-token prediction training target to achieve more powerful performance. DeepSeek-V3 is pre-trained on 14.8 trillion high-quality tokens, followed by supervised fine-tuning and reinforcement learning stages to fully exploit its capabilities. Comprehensive evaluation shows that DeepSeek-V3 outperforms other open source models and achieves comparable performance to leading closed source models. Despite the excellent performance, the complete training of DeepSeek-V3 requires only 2.788M H800 GPU hours, and the training process is very stable.

QVQ-72B-Preview is an experimental research model developed by the Qwen team, focusing on enhancing visual reasoning capabilities. The model demonstrates strong capabilities in multi-disciplinary understanding and reasoning, especially achieving significant progress in mathematical reasoning tasks. Despite the progress in visual reasoning, QVQ does not completely replace the capabilities of Qwen2-VL-72B, and may gradually lose focus on image content during multi-step visual reasoning, leading to hallucinations. Furthermore, QVQ did not show significant improvements over Qwen2-VL-72B on basic recognition tasks.

InternVL2-8B-MPO is a multimodal large language model (MLLM) that enhances the model's multimodal reasoning capabilities by introducing a mixed preference optimization (MPO) process. This model designed an automated preference data construction pipeline in terms of data, and built MMPR, a large-scale multi-modal reasoning preference data set. In terms of models, InternVL2-8B-MPO is initialized based on InternVL2-8B and fine-tuned using the MMPR data set, showing stronger multi-modal reasoning capabilities and fewer hallucinations. The model achieved an accuracy of 67.0% on MathVista, surpassing InternVL2-8B by 8.7 points, and its performance was close to InternVL2-76B, which is 10 times larger.

FlagPerf is an integrated AI hardware evaluation engine jointly built by Zhiyuan Research Institute and AI hardware manufacturers. It aims to establish an indicator system oriented by industrial practice and evaluate the actual capabilities of AI hardware under the combination of software stack (model + framework + compiler). The platform supports a multi-dimensional evaluation index system, covers large model training and inference scenarios, supports multiple training frameworks and inference engines, and connects the AI ​​hardware and software ecosystem.

Document Inlining is a composite AI system launched by Fireworks AI that can convert any large language model (LLM) into a visual model to process images or PDF documents. This technology enables logical reasoning by building an automated process to convert any digital asset format into an LLM-compatible format. Document Inlining provides higher quality, input flexibility and ultra-simple usage by parsing images and PDFs and inputting them directly into the LLM of the user's choice. It solves the limitations of traditional LLM in processing non-text data, improves the quality of text model inference through specialized component decomposition tasks, and simplifies the developer experience.

Patronus GLIDER is a fine-tuned phi-3.5-mini-instruct model that can be used as a general evaluation model to judge text, dialogue and RAG settings according to user-defined criteria and scoring rules. The model is trained using synthetic data and domain adaptation data, covering 183 indicators and 685 fields, including finance, medicine, etc. The maximum sequence length supported by the model is 8192 tokens, but has been tested to support longer text (up to 12,000 tokens).

EXAONE-3.5-7.8B-Instruct is a series of instruction-tuned bilingual (English and Korean) generative models developed by LG AI Research, with parameters ranging from 2.4B to 32B. These models support long context processing up to 32K tokens and demonstrate state-of-the-art performance in real-world use cases and long context understanding, while remaining competitive in the general domain compared to recently released models of similar size.

The OpenAI o3 model is a new generation of inference model after o1, including o3 and o3-mini versions. o3 is close to artificial general intelligence (AGI) under certain conditions, scoring as high as 87.5% on the ARC-AGI benchmark, far exceeding the human average. It performed well on math and programming tasks, scoring 96.7% in the 2024 American Invitational Mathematics Examination (AIME) and achieving a Codeforces rating of 2727. o3 is able to self-fact check and reason through "private thought chains" to improve the accuracy of answers. o3 is the first model trained using "deliberative alignment" technology to comply with safety principles. Currently, the o3 model is not widely available, but security researchers can sign up to preview the o3-mini model. The o3 mini version will be launched at the end of January, followed by the o3 full version shortly thereafter.

Voice Cursor is an experimental text editor based on Gemini 2.0's native audio capabilities, which demonstrates how Gemini's new text-to-speech API can be integrated into a text editor to enable smooth, contextual voice generation. This project not only showcases the powerful new features of Gemini 2.0, but also provides a practical application example, allowing developers and users to explore and take advantage of this new technology. Product background information includes Google Creative Lab's innovative projects designed to push the boundaries of technology and enable new ways to interact. The product is currently free and is aimed primarily at developers and technology enthusiasts, for individuals or teams looking for innovative solutions to increase productivity and accessibility.