Find and compare the best Artificial Intelligence software for Windows in 2026
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Use the comparison tool below to compare the top Artificial Intelligence software for Windows on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
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Steer
Steer
$2.49 per monthSteer is an innovative AI-driven writing assistant that aims to elevate your communication skills across various applications. It adeptly enhances and corrects your writing, ensuring that your sentences are coherent, concise, and exude professionalism. With its rapid shortcuts, Steer enables you to rectify grammar errors, enhance clarity, and polish your text without the need to switch from your current application, thus maintaining a smooth workflow. The tool automatically adjusts the tone of your messages to suit the specific context of the application you are using, whether it’s for formal or informal interactions. Compatible with any app and supporting multiple languages, Steer delivers real-time spelling and grammar corrections, allowing you to express yourself more effectively. Its lightweight and user-friendly design guarantees that it's always available to assist you without interrupting your workflow. Furthermore, Steer is compatible with both macOS and Windows, ensuring a hassle-free integration into your everyday communication practices, making it an invaluable tool for anyone looking to improve their writing efficiency. -
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AirCaption
AirCaption
$9.99 per monthAirCaption is a powerful transcription tool powered by AI, designed for both Mac and Windows users to easily transcribe audio and video files. With its operation completely offline, it prioritizes user privacy by storing all media and captions directly on the local machine. The software boasts support for transcription in as many as 67 languages, leveraging sophisticated AI models from OpenAI. Users can create captions, modify and fine-tune both text and timing, and export their work in various formats including SRT, VTT, TXT, or directly embed it into video files. AirCaption also allows users to import and adjust existing caption files while providing convenient hotkeys to enhance the editing experience. This tool is especially advantageous for a range of professionals such as video editors, podcasters, language learners, legal experts, marketers, researchers, event planners, online course developers, and journalists who seek reliable and effective transcription solutions. Additionally, AirCaption's batch processing feature empowers users to transcribe entire folders at once, making it a time-saving choice for those with large volumes of content. -
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Sky-T1
NovaSky
FreeSky-T1-32B-Preview is an innovative open-source reasoning model crafted by the NovaSky team at UC Berkeley's Sky Computing Lab. It delivers performance comparable to proprietary models such as o1-preview on various reasoning and coding assessments, while being developed at a cost of less than $450, highlighting the potential for budget-friendly, advanced reasoning abilities. Fine-tuned from Qwen2.5-32B-Instruct, the model utilized a meticulously curated dataset comprising 17,000 examples spanning multiple fields, such as mathematics and programming. The entire training process was completed in just 19 hours using eight H100 GPUs with DeepSpeed Zero-3 offloading technology. Every component of this initiative—including the data, code, and model weights—is entirely open-source, allowing both academic and open-source communities to not only replicate but also improve upon the model's capabilities. This accessibility fosters collaboration and innovation in the realm of artificial intelligence research and development. -
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Telosis
Telosis
FreeTelosis is an innovative productivity application driven by AI, aimed at assisting users in achieving deep work by differentiating between effective and ineffective tasks. The tool features an intuitive interface that allows users to effortlessly enter their assignments along with the time they wish to dedicate to them, making it easier to establish work goals. It sends immediate and precise alerts to help users stay aware of potential distractions, which helps maintain concentration throughout their working hours. Moreover, Telosis supplies detailed analytics on performance, allowing users to evaluate and improve their focus and productivity over time. This useful tool can be downloaded for free on Apple devices, making it accessible for a wide range of users eager to enhance their work habits. Whether you're a student or a professional, Telosis can support your journey towards optimizing productivity. -
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Reachy
Reachy
$49/Month/ Seat Reachy serves as an intelligent LinkedIn outreach solution that streamlines and enhances the growth of your professional network and client acquisition efforts. This tool allows users to automate their outreach on LinkedIn, making it simple to discover leads, collaborators, and potential hires. One of its standout features is the signals-based search, which helps identify prospects based on their online activities such as attending events, joining groups, and engaging with posts. Reachy also facilitates the management of multiple LinkedIn accounts within a single campaign, allowing for an unlimited number of connection requests through a smart auto-rotation system, while leveraging AI to generate tailored messages that boost engagement rates. As a desktop application, Reachy is designed to emulate human behavior, thereby minimizing the likelihood of triggering LinkedIn's restrictions, all while safeguarding user privacy by handling data locally. This platform has garnered praise from over 4,200 professionals, who recognize its capability to effectively foster partnerships, recruit talent, and automate lead generation. By utilizing Reachy, users can significantly optimize their outreach processes and achieve their networking goals with greater efficiency. -
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ExcelMaster.ai
ExcelMaster.ai
$1 per monthExcelMaster.ai serves as an AI-driven assistant for Excel that understands the intricacies of real-world table structures, allowing users to create precise formulas and automate various tasks with ease through conversational interactions. Its capabilities extend to managing intricate formulas, VBA, and Python tasks, outperforming competitors such as Copilot and ChatGPT when it comes to tackling data processing challenges. The platform features a dedicated VBA Assistant for developing and fine-tuning personalized VBA code, a Formula Assistant designed for accurate formula generation, and Cell AI functionalities that include classification, keyword extraction, format conversion, sentiment analysis, and real-time translation. Additionally, ExcelMaster.ai offers robust data cleaning and preparation tools that allow users to manipulate, cleanse, and transform their data without requiring any coding skills, effectively reducing preparation time by up to 90%. Supporting both Windows Excel 2007 or later and a web-based version, the software guarantees versatility and accessibility across multiple platforms. With its comprehensive suite of features, ExcelMaster.ai positions itself as an essential tool for users seeking to enhance their productivity in data management tasks. -
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Llama Stack
Meta
FreeLlama Stack is an innovative modular framework aimed at simplifying the creation of applications that utilize Meta's Llama language models. It features a client-server architecture with adaptable configurations, giving developers the ability to combine various providers for essential components like inference, memory, agents, telemetry, and evaluations. This framework comes with pre-configured distributions optimized for a range of deployment scenarios, facilitating smooth transitions from local development to live production settings. Developers can engage with the Llama Stack server through client SDKs that support numerous programming languages, including Python, Node.js, Swift, and Kotlin. In addition, comprehensive documentation and sample applications are made available to help users efficiently construct and deploy applications based on the Llama framework. The combination of these resources aims to empower developers to build robust, scalable applications with ease. -
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Janus-Pro-7B
DeepSeek
FreeJanus-Pro-7B is a groundbreaking open-source multimodal AI model developed by DeepSeek, expertly crafted to both comprehend and create content involving text, images, and videos. Its distinctive autoregressive architecture incorporates dedicated pathways for visual encoding, which enhances its ability to tackle a wide array of tasks, including text-to-image generation and intricate visual analysis. Demonstrating superior performance against rivals such as DALL-E 3 and Stable Diffusion across multiple benchmarks, it boasts scalability with variants ranging from 1 billion to 7 billion parameters. Released under the MIT License, Janus-Pro-7B is readily accessible for use in both academic and commercial contexts, marking a substantial advancement in AI technology. Furthermore, this model can be utilized seamlessly on popular operating systems such as Linux, MacOS, and Windows via Docker, broadening its reach and usability in various applications. -
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DeepSeekMath
DeepSeek
FreeDeepSeekMath is an advanced 7B parameter language model created by DeepSeek-AI, specifically engineered to enhance mathematical reasoning capabilities within open-source language models. Building upon the foundation of DeepSeek-Coder-v1.5, this model undergoes additional pre-training utilizing 120 billion math-related tokens gathered from Common Crawl, complemented by data from natural language and coding sources. It has shown exceptional outcomes, achieving a score of 51.7% on the challenging MATH benchmark without relying on external tools or voting systems, positioning itself as a strong contender against models like Gemini-Ultra and GPT-4. The model's prowess is further bolstered by a carefully curated data selection pipeline and the implementation of Group Relative Policy Optimization (GRPO), which improves both its mathematical reasoning skills and efficiency in memory usage. DeepSeekMath is offered in various formats including base, instruct, and reinforcement learning (RL) versions, catering to both research and commercial interests, and is intended for individuals eager to delve into or leverage sophisticated mathematical problem-solving in the realm of artificial intelligence. Its versatility makes it a valuable resource for researchers and practitioners alike, driving innovation in AI-driven mathematics. -
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DeepSeek-V2
DeepSeek
FreeDeepSeek-V2 is a cutting-edge Mixture-of-Experts (MoE) language model developed by DeepSeek-AI, noted for its cost-effective training and high-efficiency inference features. It boasts an impressive total of 236 billion parameters, with only 21 billion active for each token, and is capable of handling a context length of up to 128K tokens. The model utilizes advanced architectures such as Multi-head Latent Attention (MLA) to optimize inference by minimizing the Key-Value (KV) cache and DeepSeekMoE to enable economical training through sparse computations. Compared to its predecessor, DeepSeek 67B, this model shows remarkable improvements, achieving a 42.5% reduction in training expenses, a 93.3% decrease in KV cache size, and a 5.76-fold increase in generation throughput. Trained on an extensive corpus of 8.1 trillion tokens, DeepSeek-V2 demonstrates exceptional capabilities in language comprehension, programming, and reasoning tasks, positioning it as one of the leading open-source models available today. Its innovative approach not only elevates its performance but also sets new benchmarks within the field of artificial intelligence. -
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Falcon Mamba 7B
Technology Innovation Institute (TII)
FreeFalcon Mamba 7B marks a significant milestone as the inaugural open-source State Space Language Model (SSLM), presenting a revolutionary architecture within the Falcon model family. Celebrated as the premier open-source SSLM globally by Hugging Face, it establishes a new standard for efficiency in artificial intelligence. In contrast to conventional transformers, SSLMs require significantly less memory and can produce lengthy text sequences seamlessly without extra resource demands. Falcon Mamba 7B outperforms top transformer models, such as Meta’s Llama 3.1 8B and Mistral’s 7B, demonstrating enhanced capabilities. This breakthrough not only highlights Abu Dhabi’s dedication to pushing the boundaries of AI research but also positions the region as a pivotal player in the global AI landscape. Such advancements are vital for fostering innovation and collaboration in technology. -
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Falcon 2
Technology Innovation Institute (TII)
FreeFalcon 2 11B is a versatile AI model that is open-source, supports multiple languages, and incorporates multimodal features, particularly excelling in vision-to-language tasks. It outperforms Meta’s Llama 3 8B and matches the capabilities of Google’s Gemma 7B, as validated by the Hugging Face Leaderboard. In the future, the development plan includes adopting a 'Mixture of Experts' strategy aimed at significantly improving the model's functionalities, thereby advancing the frontiers of AI technology even further. This evolution promises to deliver remarkable innovations, solidifying Falcon 2's position in the competitive landscape of artificial intelligence. -
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Falcon 3
Technology Innovation Institute (TII)
FreeFalcon 3 is a large language model that has been made open-source by the Technology Innovation Institute (TII), aiming to broaden access to advanced AI capabilities. Its design prioritizes efficiency, enabling it to function effectively on lightweight devices like laptops while maintaining high performance levels. The Falcon 3 suite includes four scalable models, each specifically designed for various applications and capable of supporting multiple languages while minimizing resource consumption. This new release in TII's LLM lineup sets a benchmark in reasoning, language comprehension, instruction adherence, coding, and mathematical problem-solving. By offering a blend of robust performance and resource efficiency, Falcon 3 seeks to democratize AI access, allowing users in numerous fields to harness sophisticated technology without the necessity for heavy computational power. Furthermore, this initiative not only enhances individual capabilities but also fosters innovation across different sectors by making advanced AI tools readily available. -
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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. -
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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. -
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Hathr AI
Hathr AI
$45/month HIPAA-compliant AI chat solutions, API access, and enterprise-grade tools—powered by Anthropic’s Claude—Hathr AI enables healthcare providers, insurers, and professionals handling HIPAA-regulated data to streamline workflows while maintaining strict data security. Built within AWS GovCloud’s FedRAMP High environment, Hathr AI ensures all data interactions remain private and safeguarded from unauthorized access. Users can automate key processes like patient note summarization, pre-authorization drafting, and insurance claim submissions, all within a secure and intuitive platform. By leveraging advanced models such as Claude 3.5 Sonnet, Hathr AI delivers a private AI environment tailored for HIPAA compliance. Teams can efficiently extract and summarize data from complex medical records, supporting more informed clinical and administrative decisions. -
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CaptchaSonic
CaptchaSonic
$5/month CaptchaSonic, a SaaS powered by AI, is a SaaS Service that specializes in solving CAPTCHA challenges. This includes reCAPTCHA and AWS CAPTCHA. It also includes Geetest, PopularCaptcha and Lemin. We enable businesses to automate data scraping and web form submission workflows through automated CAPTCHA solving. Our services are geared towards individuals and organizations who want to find a reliable, inclusive and efficient way to interact with websites relying on CAPTCHA as a security measure. We are reliable because we have 99% uptime. Key Features - Advanced Captcha Solution API SDK - Robust and Capable Chrome and Firefox Based Browser Extensions - Prebuilt Modules and Third Party Integrations for a smooth and quick start to any project. -
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Sonar
Perplexity
FreePerplexity has unveiled a new and improved AI search engine called Sonar, which is based on the Llama 3.3 70B model. This iteration of Sonar has received further training aimed at boosting the accuracy of facts and the clarity of responses in the standard search mode offered by Perplexity. The goal of these enhancements is to provide users with more accurate and easily understandable answers, all while preserving the platform's renowned speed and efficiency. Additionally, Sonar features capabilities for real-time, expansive web research and question-answering, which developers can seamlessly incorporate into their applications via an API that is both lightweight and cost-effective. Furthermore, the Sonar API accommodates advanced models such as sonar-reasoning-pro and sonar-pro, specifically designed to tackle intricate tasks that necessitate a profound understanding and retention of context. These sophisticated models are capable of delivering more comprehensive answers, offering an average of twice the citations compared to earlier versions, thus significantly improving the transparency and dependability of the information presented. With these updates, Sonar positions itself as a leader in providing users with high-quality search experiences. -
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scalerX.ai
scalerX.ai
$5/month Launch & train personalized AI-RAG Agents on Telegram. You can create RAG AI-powered personalized agents in minutes with scalerX, and they will be trained using your knowledge base. These AI agents can be integrated directly into Telegram including groups and channels. This is great for education, customer service, entertainment and sales. It also automates community moderation. Agents can act as chatbots for solo, groups, and channels. They support text-to text, text-to image, and voice. ACLs allow you to set up agent usage quotas, and permissions for authorized users. It's easy to train your agents: Create your agent, upload files to the bots knowledgebase, or auto-sync Dropbox, Google Drive, or scrape webpages. -
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R1 1776
Perplexity AI
FreePerplexity AI has released R1 1776 as an open-source large language model (LLM), built on the DeepSeek R1 framework, with the goal of improving transparency and encouraging collaborative efforts in the field of AI development. With this release, researchers and developers can explore the model's architecture and underlying code, providing them the opportunity to enhance and tailor it for diverse use cases. By making R1 1776 available to the public, Perplexity AI seeks to drive innovation while upholding ethical standards in the AI sector. This initiative not only empowers the community but also fosters a culture of shared knowledge and responsibility among AI practitioners. -
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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. -
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LexVec
Alexandre Salle
FreeLexVec represents a cutting-edge word embedding technique that excels in various natural language processing applications by factorizing the Positive Pointwise Mutual Information (PPMI) matrix through the use of stochastic gradient descent. This methodology emphasizes greater penalties for mistakes involving frequent co-occurrences while also addressing negative co-occurrences. Users can access pre-trained vectors, which include a massive common crawl dataset featuring 58 billion tokens and 2 million words represented in 300 dimensions, as well as a dataset from English Wikipedia 2015 combined with NewsCrawl, comprising 7 billion tokens and 368,999 words in the same dimensionality. Evaluations indicate that LexVec either matches or surpasses the performance of other models, such as word2vec, particularly in word similarity and analogy assessments. The project's implementation is open-source, licensed under the MIT License, and can be found on GitHub, facilitating broader use and collaboration within the research community. Furthermore, the availability of these resources significantly contributes to advancing the field of natural language processing. -
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GloVe
Stanford NLP
FreeGloVe, which stands for Global Vectors for Word Representation, is an unsupervised learning method introduced by the Stanford NLP Group aimed at creating vector representations for words. By examining the global co-occurrence statistics of words in a specific corpus, it generates word embeddings that form vector spaces where geometric relationships indicate semantic similarities and distinctions between words. One of GloVe's key strengths lies in its capability to identify linear substructures in the word vector space, allowing for vector arithmetic that effectively communicates relationships. The training process utilizes the non-zero entries of a global word-word co-occurrence matrix, which tracks the frequency with which pairs of words are found together in a given text. This technique makes effective use of statistical data by concentrating on significant co-occurrences, ultimately resulting in rich and meaningful word representations. Additionally, pre-trained word vectors can be accessed for a range of corpora, such as the 2014 edition of Wikipedia, enhancing the model's utility and applicability across different contexts. This adaptability makes GloVe a valuable tool for various natural language processing tasks. -
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Gensim
Radim Řehůřek
FreeGensim is an open-source Python library that specializes in unsupervised topic modeling and natural language processing, with an emphasis on extensive semantic modeling. It supports the development of various models, including Word2Vec, FastText, Latent Semantic Analysis (LSA), and Latent Dirichlet Allocation (LDA), which aids in converting documents into semantic vectors and in identifying documents that are semantically linked. With a strong focus on performance, Gensim features highly efficient implementations crafted in both Python and Cython, enabling it to handle extremely large corpora through the use of data streaming and incremental algorithms, which allows for processing without the need to load the entire dataset into memory. This library operates independently of the platform, functioning seamlessly on Linux, Windows, and macOS, and is distributed under the GNU LGPL license, making it accessible for both personal and commercial applications. Its popularity is evident, as it is employed by thousands of organizations on a daily basis, has received over 2,600 citations in academic works, and boasts more than 1 million downloads each week, showcasing its widespread impact and utility in the field. Researchers and developers alike have come to rely on Gensim for its robust features and ease of use. -
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NLTK
NLTK
FreeThe Natural Language Toolkit (NLTK) is a robust, open-source library for Python, specifically created for the processing of human language data. It features intuitive interfaces to more than 50 corpora and lexical resources, including WordNet, coupled with a variety of text processing libraries that facilitate tasks such as classification, tokenization, stemming, tagging, parsing, and semantic reasoning. Additionally, NLTK includes wrappers for powerful commercial NLP libraries and hosts an active forum for discussion among users. Accompanied by a practical guide that merges programming basics with computational linguistics concepts, along with detailed API documentation, NLTK caters to a wide audience, including linguists, engineers, students, educators, researchers, and professionals in the industry. This library is compatible across various operating systems, including Windows, Mac OS X, and Linux. Remarkably, NLTK is a free project that thrives on community contributions, ensuring continuous development and support. Its extensive resources make it an invaluable tool for anyone interested in the field of natural language processing.
