Find and compare the best Artificial Intelligence software for Hugging Face in 2025
Sort:
Use the comparison tool below to compare the top Artificial Intelligence software for Hugging Face on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
-
1
FauxPilot
FauxPilot
FreeFauxPilot serves as an open-source, self-hosted substitute for GitHub Copilot, leveraging the SalesForce CodeGen models. It operates on NVIDIA's Triton Inference Server, utilizing the FasterTransformer backend to facilitate local code generation. The installation process necessitates Docker and an NVIDIA GPU with adequate VRAM, along with the capability to distribute the model across multiple GPUs if required. Users must download models from Hugging Face and perform conversions to ensure compatibility with FasterTransformer. This alternative not only provides flexibility for developers but also promotes an independent coding environment. -
2
Qwen2.5-Max
Alibaba
FreeQwen2.5-Max is an advanced Mixture-of-Experts (MoE) model created by the Qwen team, which has been pretrained on an extensive dataset of over 20 trillion tokens and subsequently enhanced through methods like Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF). Its performance in evaluations surpasses that of models such as DeepSeek V3 across various benchmarks, including Arena-Hard, LiveBench, LiveCodeBench, and GPQA-Diamond, while also achieving strong results in other tests like MMLU-Pro. This model is available through an API on Alibaba Cloud, allowing users to easily integrate it into their applications, and it can also be interacted with on Qwen Chat for a hands-on experience. With its superior capabilities, Qwen2.5-Max represents a significant advancement in AI model technology. -
3
Qwen2.5-VL
Alibaba
FreeQwen2.5-VL marks the latest iteration in the Qwen vision-language model series, showcasing notable improvements compared to its predecessor, Qwen2-VL. This advanced model demonstrates exceptional capabilities in visual comprehension, adept at identifying a diverse range of objects such as text, charts, and various graphical elements within images. Functioning as an interactive visual agent, it can reason and effectively manipulate tools, making it suitable for applications involving both computer and mobile device interactions. Furthermore, Qwen2.5-VL is proficient in analyzing videos that are longer than one hour, enabling it to identify pertinent segments within those videos. The model also excels at accurately locating objects in images by creating bounding boxes or point annotations and supplies well-structured JSON outputs for coordinates and attributes. It provides structured data outputs for documents like scanned invoices, forms, and tables, which is particularly advantageous for industries such as finance and commerce. Offered in both base and instruct configurations across 3B, 7B, and 72B models, Qwen2.5-VL can be found on platforms like Hugging Face and ModelScope, further enhancing its accessibility for developers and researchers alike. This model not only elevates the capabilities of vision-language processing but also sets a new standard for future developments in the field. -
4
Zyphra Zonos
Zyphra
$0.02 per minuteZyphra is thrilled to unveil the beta release of Zonos-v0.1, which boasts two sophisticated and real-time text-to-speech models that include high-fidelity voice cloning capabilities. Our release features both a 1.6B transformer and a 1.6B hybrid model, all under the Apache 2.0 license. Given the challenges in quantitatively assessing audio quality, we believe that the generation quality produced by Zonos is on par with or even surpasses that of top proprietary TTS models currently available. Additionally, we are confident that making models of this quality publicly accessible will greatly propel advancements in TTS research. You can find the Zonos model weights on Huggingface, with sample inference code available on our GitHub repository. Furthermore, Zonos can be utilized via our model playground and API, which offers straightforward and competitive flat-rate pricing options. To illustrate the performance of Zonos, we have prepared a variety of sample comparisons between Zonos and existing proprietary models, highlighting its capabilities. This initiative emphasizes our commitment to fostering innovation in the field of text-to-speech technology. -
5
txtai
NeuML
Freetxtai is a comprehensive open-source embeddings database that facilitates semantic search, orchestrates large language models, and streamlines language model workflows. It integrates sparse and dense vector indexes, graph networks, and relational databases, creating a solid infrastructure for vector search while serving as a valuable knowledge base for applications involving LLMs. Users can leverage txtai to design autonomous agents, execute retrieval-augmented generation strategies, and create multi-modal workflows. Among its standout features are support for vector search via SQL, integration with object storage, capabilities for topic modeling, graph analysis, and the ability to index multiple modalities. It enables the generation of embeddings from a diverse range of data types including text, documents, audio, images, and video. Furthermore, txtai provides pipelines driven by language models to manage various tasks like LLM prompting, question-answering, labeling, transcription, translation, and summarization, thereby enhancing the efficiency of these processes. This innovative platform not only simplifies complex workflows but also empowers developers to harness the full potential of AI technologies. -
6
Patched
Patched
$99 per monthPatched is a managed service that utilizes the open-source Patchwork framework to streamline various development tasks, including code reviews, bug fixes, security updates, and documentation efforts. By harnessing the capabilities of large language models, Patched empowers developers to create and implement AI-driven workflows, known as "patch flows," which automatically manage activities following code completion, ultimately improving code quality and speeding up development timelines. The platform features an intuitive graphical interface along with a visual workflow builder, which facilitates the personalization of patch flows without the burden of overseeing infrastructure or LLM endpoints. For users interested in self-hosting options, Patchwork offers a command-line interface agent that integrates effortlessly into existing development workflows. Furthermore, Patched prioritizes privacy and control, allowing organizations to deploy the service within their own infrastructure while using their specific LLM API keys. This combination of features ensures that developers can optimize their processes while maintaining a high level of security and customization. -
7
SmolLM2
Hugging Face
FreeSmolLM2 comprises an advanced suite of compact language models specifically created for on-device functionalities. This collection features models with varying sizes, including those with 1.7 billion parameters, as well as more streamlined versions at 360 million and 135 million parameters, ensuring efficient performance on even the most limited hardware. They excel in generating text and are fine-tuned for applications requiring real-time responsiveness and minimal latency, delivering high-quality outcomes across a multitude of scenarios such as content generation, coding support, and natural language understanding. The versatility of SmolLM2 positions it as an ideal option for developers aiming to incorporate robust AI capabilities into mobile devices, edge computing solutions, and other settings where resources are constrained. Its design reflects a commitment to balancing performance and accessibility, making cutting-edge AI technology more widely available. -
8
LiteLLM
LiteLLM
FreeLiteLLM serves as a comprehensive platform that simplifies engagement with more than 100 Large Language Models (LLMs) via a single, cohesive interface. It includes both a Proxy Server (LLM Gateway) and a Python SDK, which allow developers to effectively incorporate a variety of LLMs into their applications without hassle. The Proxy Server provides a centralized approach to management, enabling load balancing, monitoring costs across different projects, and ensuring that input/output formats align with OpenAI standards. Supporting a wide range of providers, this system enhances operational oversight by creating distinct call IDs for each request, which is essential for accurate tracking and logging within various systems. Additionally, developers can utilize pre-configured callbacks to log information with different tools, further enhancing functionality. For enterprise clients, LiteLLM presents a suite of sophisticated features, including Single Sign-On (SSO), comprehensive user management, and dedicated support channels such as Discord and Slack, ensuring that businesses have the resources they need to thrive. This holistic approach not only improves efficiency but also fosters a collaborative environment where innovation can flourish. -
9
EigentBot
EigentBot
$8 per monthEigentBot represents a cutting-edge intelligent agent solution that combines Retrieval-Augmented Generation (RAG) features along with robust function-call capabilities. This innovative framework allows EigentBot to adeptly handle user queries, retrieve pertinent information, and perform necessary functions, leading to precise and contextually relevant responses. By utilizing these sophisticated technologies, EigentBot is dedicated to improving user interactions across a multitude of platforms. It provides the simplest method to establish a secure and efficient AI knowledge base in mere seconds, making it an ideal tool for enhancing customer service, technical quality assurance, and beyond. Users can seamlessly transition between various AI providers without interruptions, ensuring that their AI assistant remains current with the latest and most effective models available. Additionally, EigentBot is designed to continuously refresh its knowledge base with the most recent data from trusted sources like Notion, GitHub, and Google Scholar. To further boost the accuracy of AI retrieval, EigentBot incorporates structured and visualized knowledge graphs, which significantly enhance contextual comprehension, ultimately resulting in a more intuitive user experience. -
10
Axolotl
Axolotl
FreeAxolotl is an innovative open-source tool crafted to enhance the fine-tuning process of a variety of AI models, accommodating numerous configurations and architectures. This platform empowers users to train models using diverse methods such as full fine-tuning, LoRA, QLoRA, ReLoRA, and GPTQ. Additionally, users have the flexibility to customize their configurations through straightforward YAML files or by employing command-line interface overrides, while also being able to load datasets in various formats, whether custom or pre-tokenized. Axolotl seamlessly integrates with cutting-edge technologies, including xFormers, Flash Attention, Liger kernel, RoPE scaling, and multipacking, and it is capable of operating on single or multiple GPUs using Fully Sharded Data Parallel (FSDP) or DeepSpeed. Whether run locally or in the cloud via Docker, it offers robust support for logging results and saving checkpoints to multiple platforms, ensuring users can easily track their progress. Ultimately, Axolotl aims to make the fine-tuning of AI models not only efficient but also enjoyable, all while maintaining a high level of functionality and scalability. With its user-friendly design, it invites both novices and experienced practitioners to explore the depths of AI model training. -
11
Skott
Lyzr AI
$99 per monthSkott functions as an autonomous AI marketing agent that takes care of researching, writing, and posting content, which enables your team to dedicate more time to strategic planning and creative projects. It features a customizable user interface and workflow that delivers actionable insights to shape your strategy, helps you stay ahead of industry trends through real-time data, provides thorough competitive analysis, and offers audience insights to effectively customize your content. Skott shines in producing exceptional content, including impactful blog articles, captivating social media posts, and SEO-friendly writing, while ensuring a uniform brand voice across various platforms. Furthermore, it facilitates smooth publishing by allowing you to post across multiple channels with ease, maintain consistent formatting and optimization, automate scheduling tasks, and integrate seamlessly with leading blogging and social media platforms. In addition to these features, Skott presents a cost-effective solution, delivering high-quality marketing services that enhance your return on investment without the need for excessive spending or additional hires. With its robust functionality, Skott empowers your marketing efforts, ultimately driving growth and engagement for your brand. -
12
Mistral Small 3.1
Mistral
FreeMistral Small 3.1 represents a cutting-edge, multimodal, and multilingual AI model that has been released under the Apache 2.0 license. This upgraded version builds on Mistral Small 3, featuring enhanced text capabilities and superior multimodal comprehension, while also accommodating an extended context window of up to 128,000 tokens. It demonstrates superior performance compared to similar models such as Gemma 3 and GPT-4o Mini, achieving impressive inference speeds of 150 tokens per second. Tailored for adaptability, Mistral Small 3.1 shines in a variety of applications, including instruction following, conversational support, image analysis, and function execution, making it ideal for both business and consumer AI needs. The model's streamlined architecture enables it to operate efficiently on hardware such as a single RTX 4090 or a Mac equipped with 32GB of RAM, thus supporting on-device implementations. Users can download it from Hugging Face and access it through Mistral AI's developer playground, while it is also integrated into platforms like Google Cloud Vertex AI, with additional accessibility on NVIDIA NIM and more. This flexibility ensures that developers can leverage its capabilities across diverse environments and applications. -
13
ML Console
ML Console
FreeML Console is an innovative web application that empowers users to develop robust machine learning models effortlessly, without the need for coding skills. It is tailored for a diverse range of users, including those in marketing, e-commerce, and large organizations, enabling them to construct AI models in under a minute. The application functions entirely in the browser, which keeps user data private and secure. Utilizing cutting-edge web technologies such as WebAssembly and WebGL, ML Console delivers training speeds that rival those of traditional Python-based approaches. Its intuitive interface streamlines the machine learning experience, making it accessible to individuals regardless of their expertise level in AI. Moreover, ML Console is available at no cost, removing obstacles for anyone interested in delving into the world of machine learning solutions. By democratizing access to powerful AI tools, it opens up new possibilities for innovation across various industries. -
14
Pruna AI
Pruna AI
$0.40 per runtime hourPruna leverages generative AI technology to help businesses generate high-quality visual content swiftly and cost-effectively. It removes the conventional requirements for studios and manual editing processes, allowing brands to effortlessly create tailored and uniform images for advertising, product showcases, and online campaigns. This innovation significantly streamlines the content creation process, enhancing efficiency and creativity for various marketing needs. -
15
Hugging Face Transformers
Hugging Face
$9 per monthTransformers is a versatile library that includes pretrained models for natural language processing, computer vision, audio, and multimodal tasks, facilitating both inference and training. With the Transformers library, you can effectively train models tailored to your specific data, create inference applications, and utilize large language models for text generation. Visit the Hugging Face Hub now to discover a suitable model and leverage Transformers to kickstart your projects immediately. This library provides a streamlined and efficient inference class that caters to various machine learning tasks, including text generation, image segmentation, automatic speech recognition, and document question answering, among others. Additionally, it features a robust trainer that incorporates advanced capabilities like mixed precision, torch.compile, and FlashAttention, making it ideal for both training and distributed training of PyTorch models. The library ensures rapid text generation through large language models and vision-language models, and each model is constructed from three fundamental classes (configuration, model, and preprocessor), allowing for quick deployment in either inference or training scenarios. Overall, Transformers empowers users with the tools needed to create sophisticated machine learning solutions with ease and efficiency. -
16
Qwen3
Alibaba
FreeQwen3 is a state-of-the-art large language model designed to revolutionize the way we interact with AI. Featuring both thinking and non-thinking modes, Qwen3 allows users to customize its response style, ensuring optimal performance for both complex reasoning tasks and quick inquiries. With the ability to support 119 languages, the model is suitable for international projects. The model's hybrid training approach, which involves over 36 trillion tokens, ensures accuracy across a variety of disciplines, from coding to STEM problems. Its integration with platforms such as Hugging Face, ModelScope, and Kaggle allows for easy adoption in both research and production environments. By enhancing multilingual support and incorporating advanced AI techniques, Qwen3 is designed to push the boundaries of AI-driven applications. -
17
Flower
Flower
FreeFlower is a federated learning framework that is open-source and aims to make the creation and implementation of machine learning models across distributed data sources more straightforward. By enabling the training of models on data stored on individual devices or servers without the need to transfer that data, it significantly boosts privacy and minimizes bandwidth consumption. The framework is compatible with an array of popular machine learning libraries such as PyTorch, TensorFlow, Hugging Face Transformers, scikit-learn, and XGBoost, and it works seamlessly with various cloud platforms including AWS, GCP, and Azure. Flower offers a high degree of flexibility with its customizable strategies and accommodates both horizontal and vertical federated learning configurations. Its architecture is designed for scalability, capable of managing experiments that involve tens of millions of clients effectively. Additionally, Flower incorporates features geared towards privacy preservation, such as differential privacy and secure aggregation, ensuring that sensitive data remains protected throughout the learning process. This comprehensive approach makes Flower a robust choice for organizations looking to leverage federated learning in their machine learning initiatives. -
18
Open Computer Agent
Hugging Face
FreeThe Open Computer Agent is an AI assistant that operates within a web browser, created by Hugging Face, designed to automate tasks like web browsing, filling out forms, and retrieving information. Utilizing advanced vision-language models such as Qwen-VL, it mimics mouse and keyboard actions, allowing it to perform a variety of functions, from booking tickets to checking operating hours and navigating to locations. The agent can effectively identify and engage with various elements on web pages by analyzing their image coordinates. As part of the smolagents initiative by Hugging Face, it prioritizes both flexibility and transparency, providing an open-source framework for developers to explore, alter, and expand for specialized uses. Although still in the developmental phase and encountering certain obstacles, this agent signifies a pioneering shift toward AI functioning as a proactive digital assistant, adept at executing online tasks independently without requiring direct user involvement. Furthermore, its ongoing evolution may lead to even greater possibilities in automating complex web interactions in the future. -
19
Devstral
Mistral AI
$0.1 per million input tokensDevstral is a collaborative effort between Mistral AI and All Hands AI, resulting in an open-source large language model specifically tailored for software engineering. This model demonstrates remarkable proficiency in navigating intricate codebases, managing edits across numerous files, and addressing practical problems, achieving a notable score of 46.8% on the SWE-Bench Verified benchmark, which is superior to all other open-source models. Based on Mistral-Small-3.1, Devstral boasts an extensive context window supporting up to 128,000 tokens. It is designed for optimal performance on high-performance hardware setups, such as Macs equipped with 32GB of RAM or Nvidia RTX 4090 GPUs, and supports various inference frameworks including vLLM, Transformers, and Ollama. Released under the Apache 2.0 license, Devstral is freely accessible on platforms like Hugging Face, Ollama, Kaggle, Unsloth, and LM Studio, allowing developers to integrate its capabilities into their projects seamlessly. This model not only enhances productivity for software engineers but also serves as a valuable resource for anyone working with code. -
20
BGE
BGE
FreeBGE (BAAI General Embedding) serves as a versatile retrieval toolkit aimed at enhancing search capabilities and Retrieval-Augmented Generation (RAG) applications. It encompasses functionalities for inference, evaluation, and fine-tuning of embedding models and rerankers, aiding in the creation of sophisticated information retrieval systems. This toolkit features essential elements such as embedders and rerankers, which are designed to be incorporated into RAG pipelines, significantly improving the relevance and precision of search results. BGE accommodates a variety of retrieval techniques, including dense retrieval, multi-vector retrieval, and sparse retrieval, allowing it to adapt to diverse data types and retrieval contexts. Users can access the models via platforms like Hugging Face, and the toolkit offers a range of tutorials and APIs to help implement and customize their retrieval systems efficiently. By utilizing BGE, developers are empowered to construct robust, high-performing search solutions that meet their unique requirements, ultimately enhancing user experience and satisfaction. Furthermore, the adaptability of BGE ensures it can evolve alongside emerging technologies and methodologies in the data retrieval landscape. -
21
Pinecone Rerank v0
Pinecone
$25 per monthPinecone Rerank V0 is a cross-encoder model specifically designed to enhance precision in reranking tasks, thereby improving enterprise search and retrieval-augmented generation (RAG) systems. This model processes both queries and documents simultaneously, enabling it to assess fine-grained relevance and assign a relevance score ranging from 0 to 1 for each query-document pair. With a maximum context length of 512 tokens, it ensures that the quality of ranking is maintained. In evaluations based on the BEIR benchmark, Pinecone Rerank V0 stood out by achieving the highest average NDCG@10, surpassing other competing models in 6 out of 12 datasets. Notably, it achieved an impressive 60% increase in performance on the Fever dataset when compared to Google Semantic Ranker, along with over 40% improvement on the Climate-Fever dataset against alternatives like cohere-v3-multilingual and voyageai-rerank-2. Accessible via Pinecone Inference, this model is currently available to all users in a public preview, allowing for broader experimentation and feedback. Its design reflects an ongoing commitment to innovation in search technology, making it a valuable tool for organizations seeking to enhance their information retrieval capabilities. -
22
RankGPT
Weiwei Sun
FreeRankGPT is a Python toolkit specifically crafted to delve into the application of generative Large Language Models (LLMs), such as ChatGPT and GPT-4, for the purpose of relevance ranking within Information Retrieval (IR). It presents innovative techniques, including instructional permutation generation and a sliding window strategy, which help LLMs to efficiently rerank documents. Supporting a diverse array of LLMs—including GPT-3.5, GPT-4, Claude, Cohere, and Llama2 through LiteLLM—RankGPT offers comprehensive modules for retrieval, reranking, evaluation, and response analysis, thereby streamlining end-to-end processes. Additionally, the toolkit features a module dedicated to the in-depth analysis of input prompts and LLM outputs, effectively tackling reliability issues associated with LLM APIs and the non-deterministic nature of Mixture-of-Experts (MoE) models. Furthermore, it is designed to work with multiple backends, such as SGLang and TensorRT-LLM, making it compatible with a broad spectrum of LLMs. Among its resources, RankGPT's Model Zoo showcases various models, including LiT5 and MonoT5, which are conveniently hosted on Hugging Face, allowing users to easily access and implement them in their projects. Overall, RankGPT serves as a versatile and powerful toolkit for researchers and developers aiming to enhance the effectiveness of information retrieval systems through advanced LLM techniques. -
23
HumanSignal
HumanSignal
$99 per monthHumanSignal's Label Studio Enterprise is a versatile platform crafted to produce high-quality labeled datasets and assess model outputs with oversight from human evaluators. This platform accommodates the labeling and evaluation of diverse data types, including images, videos, audio, text, and time series, all within a single interface. Users can customize their labeling environments through pre-existing templates and robust plugins, which allows for the adaptation of user interfaces and workflows to meet specific requirements. Moreover, Label Studio Enterprise integrates effortlessly with major cloud storage services and various ML/AI models, thus streamlining processes such as pre-annotation, AI-assisted labeling, and generating predictions for model assessment. The innovative Prompts feature allows users to utilize large language models to quickly create precise predictions, facilitating the rapid labeling of thousands of tasks. Its capabilities extend to multiple labeling applications, encompassing text classification, named entity recognition, sentiment analysis, summarization, and image captioning, making it an essential tool for various industries. Additionally, the platform's user-friendly design ensures that teams can efficiently manage their data labeling projects while maintaining high standards of accuracy. -
24
FriendliAI
FriendliAI
$5.9 per hourFriendliAI serves as an advanced generative AI infrastructure platform that delivers rapid, efficient, and dependable inference solutions tailored for production settings. The platform is equipped with an array of tools and services aimed at refining the deployment and operation of large language models (LLMs) alongside various generative AI tasks on a large scale. Among its key features is Friendli Endpoints, which empowers users to create and implement custom generative AI models, thereby reducing GPU expenses and hastening AI inference processes. Additionally, it facilitates smooth integration with well-known open-source models available on the Hugging Face Hub, ensuring exceptionally fast and high-performance inference capabilities. FriendliAI incorporates state-of-the-art technologies, including Iteration Batching, the Friendli DNN Library, Friendli TCache, and Native Quantization, all of which lead to impressive cost reductions (ranging from 50% to 90%), a significant decrease in GPU demands (up to 6 times fewer GPUs), enhanced throughput (up to 10.7 times), and a marked decrease in latency (up to 6.2 times). With its innovative approach, FriendliAI positions itself as a key player in the evolving landscape of generative AI solutions. -
25
ZenCtrl
Fotographer AI
FreeZenCtrl is an innovative, open-source AI image generation toolkit created by Fotographer AI, aimed at generating high-quality, multi-perspective visuals from a single image without requiring any form of training. This tool allows for precise regeneration of objects and subjects viewed from various angles and backgrounds, offering real-time element regeneration which enhances both stability and flexibility in creative workflows. Users can easily regenerate subjects from different perspectives, swap backgrounds or outfits with a simple click, and start producing results instantly without the need for prior training. By utilizing cutting-edge image processing methods, ZenCtrl guarantees high accuracy while minimizing the need for large training datasets. The architecture consists of streamlined sub-models, each specifically fine-tuned to excel at distinct tasks, resulting in a lightweight system that produces sharper and more controllable outcomes. The latest update to ZenCtrl significantly improves the generation of both subjects and backgrounds, ensuring that the final images are not only coherent but also visually appealing. This continual enhancement reflects the commitment to providing users with the most efficient and effective tools for their creative endeavors.