Best 907 AI Model Tools of 2025

EmaFusion? is an innovative AI model that integrates over 100 foundation and specialized models to deliver the highest accuracy at the lowest cost and latency. Tailored for enterprises, it ensures secure, efficient, and scalable AI applications with built-in fault tolerance and customized controls. EmaFusion? is designed to boost the efficiency of AI applications and is suitable for a wide range of business needs.

GPT-4.1 is a series of new models that offer significant performance improvements, particularly in coding, instruction following, and handling long text contexts. Its context window has been expanded to 1 million tokens, and it excels in real-world applications, making it suitable for developers to create more efficient applications. This model is relatively low-cost and offers fast response times, making it more efficient for developing and executing complex tasks.

GLM-4-32B is a high-performance generative language model designed to handle various natural language tasks. Trained using deep learning techniques, it can generate coherent text and answer complex questions. This model is suitable for academic research, commercial applications, and developers. It is reasonably priced, precisely positioned, and a leading product in the field of natural language processing.

InternVL3 is a multimodal large language model (MLLM) open-sourced by OpenGVLab, possessing superior multimodal perception and reasoning capabilities. This model series includes 7 sizes ranging from 1B to 78B parameters, capable of simultaneously processing various information types such as text, images, and videos, demonstrating excellent overall performance. InternVL3 excels in industrial image analysis and 3D visual perception, with its overall text performance even surpassing the Qwen2.5 series. The open-sourcing of this model provides strong support for multimodal application development and helps promote the application of multimodal technology in more fields.

Skywork-OR1 is a high-performance mathematical code reasoning model developed by Kunlun Wanwei's Tiangong team. This model series achieves industry-leading inference performance with comparable parameter scales, breaking through the bottleneck of large models in logical understanding and complex task solving. The Skywork-OR1 series includes three models: Skywork-OR1-Math-7B, Skywork-OR1-7B-Preview, and Skywork-OR1-32B-Preview, focusing on mathematical reasoning, general reasoning, and high-performance reasoning tasks, respectively. This open-source release not only includes model weights but also fully opens the training dataset and complete training code. All resources have been uploaded to GitHub and Hugging Face, providing the AI community with a fully reproducible practical reference. This comprehensive open-source strategy helps to promote the common progress of the entire AI community in reasoning ability research.

Kimi-VL is an advanced expert-mixed visual language model designed for multi-modal reasoning, long-context understanding, and powerful agent capabilities. This model excels in several complex domains, boasting efficient 2.8B parameters while exhibiting outstanding mathematical reasoning and image understanding capabilities. Kimi-VL sets a new standard for multi-modal models with its optimized computational performance and ability to handle long inputs.

Dream 7B is the latest diffusion large language model jointly launched by the NLP group of the University of Hong Kong and Huawei Noah's Ark Lab. It demonstrates excellent performance in text generation, especially in complex reasoning, long-term planning, and contextual coherence. The model adopts advanced training methods, possesses strong planning capabilities and flexible reasoning capabilities, and provides stronger support for various AI applications.

Llama-3.1-Nemotron-Ultra-253B-v1 is a large language model based on Llama-3.1-405B-Instruct, which has undergone multi-stage post-training to enhance reasoning and chat capabilities. This model supports context lengths up to 128K, offering a good balance between accuracy and efficiency. Suitable for commercial use, it aims to provide developers with powerful AI assistant functionality.

Step-R1-V-Mini is a new multimodal reasoning model launched by Jieyue Xingchen. It supports image and text input and text output, and has good instruction following and general capabilities. The model has been technically optimized for reasoning performance in multimodal collaborative scenarios. It employs multimodal joint reinforcement learning and a training method that makes full use of multimodal synthetic data, effectively improving the model's ability to handle complex chain processing in image space. Step-R1-V-Mini has performed brilliantly in several public leaderboards, particularly ranking first domestically in the MathVision visual reasoning leaderboard, demonstrating its excellent performance in visual reasoning, mathematical logic, and code. The model has been officially launched on the Jieyue AI web page and provides API interfaces on the Jieyue Xingchen open platform for developers and researchers to experience and use.

HiDream-I1 is a new open-source image generation base model with 17 billion parameters, capable of generating high-quality images within seconds. This model is suitable for research and development and has performed excellently in multiple evaluations, demonstrating high efficiency and flexibility, making it suitable for various creative design and generation tasks.

EasyControl is a framework that provides efficient and flexible control for Diffusion Transformer (DiT), aiming to solve the efficiency bottlenecks and lack of model adaptability in the current DiT ecosystem. Its main advantages include: supporting multiple conditional combinations, improving generation flexibility and inference efficiency. This product is developed based on the latest research results and is suitable for use in image generation, style transfer, and other fields.

QVQ-Max is a visual reasoning model launched by the Qwen team, capable of understanding and analyzing image and video content to provide solutions. It is not limited to text input but can also handle complex visual information. Suitable for users who need multi-modal information processing, such as in education, work, and life scenarios. This product is developed based on deep learning and computer vision technology and is suitable for students, professionals, and creative individuals. This is the initial release, and subsequent optimizations will be continuous.

Qwen2.5-Omni is a new generation of end-to-end multimodal flagship model launched by Alibaba Cloud's Tongyi Qianwen team. Designed for comprehensive multimodal perception, this model seamlessly handles various input formats such as text, images, audio, and video, and generates text and natural speech synthesis output simultaneously through real-time streaming responses. Its innovative Thinker-Talker architecture and TMRoPE positional encoding technology enable it to excel in multimodal tasks, especially in audio, video, and image understanding. The model surpasses similar-scale unimodal models in several benchmark tests, demonstrating powerful performance and broad application potential. Currently, Qwen2.5-Omni is open-sourced on Hugging Face, ModelScope, DashScope, and GitHub, providing developers with abundant usage scenarios and development support.

Gemini 2.5 is Google's most advanced AI model, featuring efficient reasoning and coding capabilities. It can handle complex problems and excels in various benchmark tests. This model introduces novel thinking capabilities, combining an enhanced base model with post-training to support more complex tasks, aiming to provide strong support for developers and businesses. Gemini 2.5 Pro is available in Google AI Studio and the Gemini app, suitable for users requiring advanced reasoning and coding capabilities.

DeepSeek-V3-0324 is an advanced text generation model with 68.5 billion parameters, using BF16 and F32 tensor types, enabling efficient inference and text generation. The model's main advantages lie in its powerful generation capabilities and open-source nature, allowing it to be widely applied to various natural language processing tasks. The model is positioned to provide developers and researchers with a powerful tool to help them achieve breakthroughs in the field of text generation.

HunYuan T1 is a large-scale reasoning model launched by Tencent, based on reinforcement learning technology, significantly improving reasoning capabilities through extensive post-training. It excels in long text processing and context capture, while optimizing the consumption of computing resources, thus possessing efficient reasoning capabilities. It is suitable for various reasoning tasks, and particularly excels in mathematics and logical reasoning. This product is based on deep learning and continuously optimized with actual feedback, suitable for applications in various fields such as scientific research and education.

HunYuan T1 is a deep reasoning large model based on reinforcement learning, launched by Tencent. Through extensive post-training and alignment with human preferences, it significantly improves reasoning ability and efficiency. The product is based on a large-scale Hybrid-Transformer-Mamba MoE architecture, enabling the model to perform better when handling long texts. Suitable for various users who need complex reasoning and logical solutions, assisting scientific research and technological development.

Reka Flash 3 is a 2.1 billion parameter general-purpose reasoning model trained from scratch, using synthetic and public datasets for supervised fine-tuning, combined with model-based and rule-based rewards for reinforcement learning. This model excels in low-latency and on-device deployment applications and possesses strong research capabilities. It is currently the best choice among similar open-source models and is suitable for various natural language processing tasks and application scenarios.

MC-Bench is an online platform designed to evaluate and compare different AI-generated buildings within the Minecraft game environment. It allows users to vote and participate in AI evaluation, promoting the development of AI technology. The platform's main advantages lie in its fun and interactive nature, providing users with a simple and engaging way to understand AI capabilities.

EXAONE Deep is an advanced reasoning AI model launched by LG AI Research, signifying Korea's competitiveness in the global AI market. With 3.2 billion parameters, it demonstrates outstanding performance, particularly in solving mathematical and scientific problems. The release of this model marks LG's entry into the era of autonomous decision-making in the AI field, and its open-source nature allows more developers to utilize this technology for research and development. EXAONE Deep's lightweight design and on-device model make it suitable for multiple industries, including education, scientific research, and programming.

Mistral-Small-3.1-24B-Base-2503 is an advanced open-source model with 24 billion parameters, supporting multilingual and long-context processing, suitable for text and visual tasks. It is the base model of Mistral Small 3.1, possessing strong multimodal capabilities and suitable for enterprise needs.

Light-R1-14B-DS is an open-source mathematical model developed by Qihoo 360 Technology Co., Ltd. Trained using reinforcement learning based on DeepSeek-R1-Distill-Qwen-14B, it achieved high scores of 74.0 and 60.2 on the AIME24 and AIME25 mathematics competition benchmarks, respectively, surpassing many 32B parameter models. It successfully implemented reinforcement learning on an already long-chain reasoning fine-tuned model under a lightweight budget, providing the open-source community with a powerful mathematical model tool. Its open-source nature promotes the application of natural language processing in education, particularly in mathematical problem-solving, offering researchers and developers valuable research foundations and practical tools.

Gemini Robotics is an advanced artificial intelligence model from Google DeepMind, designed for robotic applications. Based on the Gemini 2.0 architecture, it fuses vision, language, and action (VLA), enabling robots to perform complex real-world tasks. The importance of this technology lies in its advancement of robots from the laboratory to everyday life and industrial applications, laying the foundation for the future development of intelligent robots. Key advantages of Gemini Robotics include strong generalization capabilities, interactivity, and dexterity, allowing it to adapt to different tasks and environments. Currently, the technology is in the research and development phase, and specific pricing and market positioning have not yet been defined.

Selene API is an advanced AI evaluation model launched by Atla AI. Using world-leading LLM-as-a-Judge technology, it provides precise AI application evaluations. Key advantages include high accuracy and reliability, surpassing leading models across various evaluation benchmarks. It offers accurate scoring and actionable feedback to help developers optimize their AI applications. Developed by Atla AI, a company committed to building a safe AI future, Selene API currently offers a free trial and uses a usage-based pricing model.

Jamba 1.6 is AI21's latest language model, designed for private enterprise deployment. It excels in long-text processing, handling context windows up to 256K. Employing a hybrid SSM-Transformer architecture, it efficiently and accurately processes long-text question-answering tasks. This model surpasses similar models from Mistral, Meta, and Cohere in quality, while supporting flexible deployment options, including private deployment on-premise or in a VPC, ensuring data security. It offers enterprises a solution that doesn't compromise between data security and model quality, suitable for scenarios requiring extensive data and long-text processing, such as R&D, legal, and finance. Jamba 1.6 is currently used in several enterprises, such as Fnac for data classification and Educa Edtech for building personalized chatbots.

Gemma 3 is Google's latest open-source model, developed using research and technology from Gemini 2.0. It's a lightweight, high-performance model that runs on a single GPU or TPU, providing developers with powerful AI capabilities. Gemma 3 offers various sizes (1B, 4B, 12B, and 27B), supports over 140 languages, and boasts advanced text and visual reasoning capabilities. Its key advantages include high performance, low computational requirements, and extensive multilingual support, making it suitable for rapid AI application deployment on diverse devices. The launch of Gemma 3 aims to promote AI technology adoption and innovation, helping developers achieve efficient development across different hardware platforms.

AgiBot's general-purpose embodied base large model, GO-1, is a revolutionary AI model. Based on the innovative Vision-Language-Latent-Action (ViLLA) architecture, this model uses a multi-modal large model (VLM) and a Mixture-of-Experts (MoE) system to achieve efficient conversion from visual and language input to robot action execution. GO-1 can learn from human videos and real robot data, possesses strong generalization capabilities, and can quickly adapt to new tasks and environments with minimal or even zero data. Its main advantages include efficient learning ability, strong generalization performance, and adaptability to various robot bodies. The launch of this model marks a significant step towards the generalization, openness, and intelligence of embodied intelligence, and is expected to play an important role in commercial, industrial, and household applications.

Venice is an AI platform that prioritizes privacy, offering various functions such as text generation, image generation, and code generation. It emphasizes the privacy of user data; all data is stored only on the user's device and is not uploaded to a server. The platform utilizes leading open-source AI technology to provide unbiased and uncensored intelligent services, aiming to offer users a free environment to explore creativity and knowledge. Venice offers both free and paid account options; paid users can enjoy higher-resolution images, watermark-free results, unlimited prompts, and other advanced features.

OpenAI's built-in tools are a collection of features within the OpenAI platform used to enhance model capabilities. These tools allow the model to access additional context and information from the web or files when generating responses. For example, by enabling the web search tool, the model can use the latest information on the web to generate responses. The main advantages of these tools are their ability to expand model capabilities, enabling it to handle more complex tasks and requirements. The OpenAI platform provides various tools such as web search, file search, computer usage, and function calls. The use of these tools depends on the provided prompt; the model will automatically decide whether to use the configured tools based on the prompt. Additionally, users can explicitly control or guide model behavior by setting tool selection parameters. These tools are very useful in scenarios requiring real-time data or specific file content, improving the model's practicality and flexibility.

Steiner is a series of reasoning models developed by Yichao 'Peak' Ji, focusing on training on synthetic data through reinforcement learning, capable of exploring multiple paths and autonomously verifying or retracing during reasoning. The model aims to replicate the reasoning capabilities of OpenAI o1 and verify the scaling curve during reasoning. Steiner-preview is an ongoing project, and its open-source nature aims to share knowledge and obtain feedback from more real users. Although the model performs well in some benchmark tests, it has not yet fully achieved the reasoning scaling capabilities of OpenAI o1 and is therefore still under development.