Find and compare the best Artificial Intelligence software for Linux in 2026
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Use the comparison tool below to compare the top Artificial Intelligence software for Linux on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
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1
Zoom Canvas
Zoom Communications
$8.55 per monthZoom Canvas is an AI-powered collaborative document platform designed to help organizations create content, manage projects, and organize team knowledge. The software provides a flexible workspace for building documents, interactive tables, internal wikis, project trackers, and shared information hubs. Its ZoomMate AI assistant can generate document drafts, summarize meeting conversations, rewrite text, translate content, and extract action items from existing information. Users can create documents from meeting summaries and connect agendas, notes, and follow-up tasks within the same workspace. Real-time collaboration features include simultaneous editing, comments, mentions, reactions, and customizable viewing and editing permissions. Zoom Canvas provides templates and drag-and-drop content blocks for adding tables, charts, images, checklists, and embedded multimedia. Its project management capabilities include Kanban boards, calendar views, timelines, task assignments, and structured data tables with filtering and sorting. The platform also supports publishing documents to the web and organizing resources for internal teams or external collaborators. Integration with Zoom Meetings, Zoom Chat, and Zoom Whiteboard allows users to collaborate on documents during meetings and continue working on shared information afterward. -
2
AI Chatbot Support
AI Chatbot Support
$40/month AI Chatbot Support is a leader in customer service technology, offering a sophisticated fusion of autonomous AI and live chat solutions that redefine customer interactions. Our platform integrates with a wide range of communication channels, including websites, social media, and messaging apps, through an intelligent AI chatbot that continuously learns from your content and interactions. Support Dashboard AI Chatbot Support provides customer support across multiple channels. Our dashboard—accessible via web, desktop, and mobile devices—allows businesses to manage customer interactions from a single, centralized interface. To train your AI chatbot and deploy it across various channels, including your website, Facebook Messenger, Instagram, WhatsApp, Slack, Viber, Telegram, and WeChat. Try AI Chatbot Support today! -
3
Firebot
Firebot
FreeFirebot is a free and open-source bot aimed at Twitch streamers, crafted to enhance their streaming experience through interactive features and effective chat management solutions. With a sleek, user-friendly interface, it allows users to configure the bot for a multitude of functions without requiring any programming expertise. Its notable features encompass customizable chat commands, a real-time integrated chat feed for interaction and moderation, automated responses triggered by various stream events, and a currency system that incentivizes viewer participation. In addition, Firebot includes engaging built-in games such as slots and heists, along with strong moderation tools to ensure a welcoming chat atmosphere. It also supports integrations with popular platforms like Streamlabs, StreamElements, Discord, and Philips Hue to further enrich the streaming experience. As a project fueled by community contributions, Firebot is consistently updated and refined, making it a powerful and adaptable tool for streamers looking to elevate their content and engage their audiences more effectively. This ongoing collaboration within the community not only enhances the bot's features but also encourages innovation among users. -
4
SAMMI
SAMMI
FreeSAMMI (Stream Automation, Management, Monitoring & Innovation) serves as a versatile streaming assistant that allows audiences on Twitch and YouTube Live to engage with and manage live broadcasts. It works in harmony with OBS Studio through the OBS WebSocket, providing users with the capability to handle scenes, sources, and various other elements remotely. SAMMI tracks events like subscriptions and chat interactions, automates responses, and adjusts channel point rewards as needed. Its user-friendly visual programming interface lets users design buttons for anything from simple scene changes to intricate commands, all without the need for coding knowledge. The software comprises several key components, including SAMMI Core, SAMMI Bridge, SAMMI Panel, and SAMMI Voice, each fulfilling specific roles within the overall framework. Designed mainly for Windows 10 and newer versions, SAMMI also has the potential to function on Linux and macOS, utilizing compatibility layers such as Wine to enhance accessibility. This adaptability makes SAMMI a valuable tool for broadcasters aiming to elevate audience engagement and streamline their streaming experience. -
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Swagger Codegen
SmartBear
FreeSwagger Codegen streamlines your development workflow by automatically generating server stubs and client SDKs for any API outlined in the OpenAPI specification, allowing your team to concentrate more effectively on implementing and promoting your API. Transitioning from design to development is remarkably simplified when using Swagger Codegen within SwaggerHub, where you can create stubs in widely-used programming languages such as Java, Scala, and Ruby with minimal effort, requiring just a few clicks to get started. This efficiency not only saves time but also enhances collaboration among team members throughout the API lifecycle. -
6
Kiota
Microsoft
FreeKiota serves as a versatile client, plugin, and manifest generator tailored for HTTP REST APIs that are defined by OpenAPI specifications. It is accessible both as a command-line utility and a Visual Studio Code (VS Code) extension, providing developers with the ability to efficiently search through API descriptions, filter and choose specific endpoints, and create models along with a methodically chained API surface in multiple programming languages. This innovative solution reduces reliance on varied API clients for different APIs, allowing for the precise crafting of the necessary API surface area. Furthermore, Kiota contributes to the Microsoft Copilot ecosystem by supporting the generation of API plugins, thus enhancing its utility. The VS Code extension enriches the Kiota experience with an intuitive user interface that includes features such as API description searches, endpoint filtering, and client generation. Users can easily pick the endpoints they need and generate not just clients but also plugins and other outputs, all while receiving completion notifications and having straightforward access to generated outputs right within their workspace. This comprehensive functionality makes Kiota a powerful tool for streamlining API interactions and development processes. -
7
AutoRest
Microsoft
FreeAutoRest is a powerful tool that facilitates the generation of client libraries for interacting with RESTful web services. It requires a specification that outlines the REST API using the OpenAPI format, enabling the streamlined production of client code in various programming languages like C#, Java, Python, TypeScript, and Go. By automating this process, AutoRest significantly improves consistency and efficiency in API usage, thereby minimizing the manual labor involved in creating and maintaining client libraries. The tool utilizes a versatile pipeline to process OpenAPI input files, converting them into a code model that language-specific generators then use to create client code that conforms to the design principles of each language. Supporting both OpenAPI 2.0 and 3.0 specifications, AutoRest ensures broad compatibility with numerous APIs. Additionally, developers can easily install AutoRest on any major operating system, including Windows, macOS, or Linux, using the Node.js package manager for a straightforward setup experience. This accessibility makes it an invaluable resource for developers looking to streamline their API integration processes. -
8
Defang
Defang
$10 per monthDefang is a developer-focused platform designed to streamline the development, deployment, and debugging of cloud applications. Utilizing AI-driven tools, Defang empowers developers to quickly evolve their concepts into fully operational applications hosted on their selected cloud services. The platform accommodates various programming languages such as Go, JavaScript, and Python, enabling users to kickstart their projects with example templates or create outlines through natural language instructions. With just a single command, Defang automates the building and deployment processes, managing configurations related to computing, storage, load balancing, networking, logging, and security seamlessly. The Defang Command Line Interface (CLI) enhances user interaction with the platform, providing installation methods through shell scripts, Homebrew, Winget, Nix, or direct downloads. Developers can specify their services using compose.yaml files, which Defang leverages to facilitate application deployment in the cloud. Overall, this platform significantly reduces the complexity traditionally associated with cloud application development, making it more accessible for developers at all skill levels. -
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KitchenAI
KitchenAI
$17 per monthKitchenAI is a framework designed for developers that simplifies the conversion of AI Jupyter Notebooks into APIs that are ready for production use. It connects AI developers, application developers, and infrastructure developers by offering a comprehensive API server equipped with default routes, an easy-to-use command-line interface for swift setup, and a flexible plugin architecture. This innovative design empowers users to create a variety of AI methodologies, quickly test them, iterate efficiently, and share their results with ease. For AI developers, KitchenAI enhances scalability in environments they are already accustomed to, transforming notebooks into strong applications. Application developers gain from user-friendly SDKs and tools that streamline the incorporation of AI via straightforward APIs, enabling rapid testing to identify the best AI techniques for their specific needs. Additionally, infrastructure developers have the capability to seamlessly integrate with AI tools and systems, further enhancing the overall functionality and user experience. This collaborative approach fosters a more efficient development process, ultimately benefiting all parties involved. -
10
SmythOS
SmythOS
$30 per monthBid farewell to the hassles of manual coding and accelerate the creation of agents like never before. Simply articulate your requirements, and SmythOS will generate it based on your conversation or image, leveraging top-tier AI models and APIs tailored to your needs. You can utilize any AI model or API, seamlessly integrating with platforms such as OpenAI, Hugging Face, Amazon Bedrock, and countless others without needing to write a single line of code. With a library of pre-built agent templates, you can access agents that are ready to function for various use cases instantly; all it takes is a click of a button and your API keys to connect. It's essential that your marketing team does not have access to agents interacting with your code, and we ensure that protection. Establish dedicated spaces for each client, team, and project with comprehensive user and permission management capabilities. You can choose to deploy on-premises or on AWS, while integrating with Bedrock, Vertex, Adobe, Salesforce, and much more. Enjoy explainable AI with complete oversight over data flows, including audit logs, encryption, and authentication measures. You can engage in conversations with your agents, assign them bulk tasks, review their logs, set work schedules, and perform an array of additional functions to streamline your operations efficiently. This innovative approach empowers your team to focus on strategy and creativity, leaving the technical complexities to SmythOS. -
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MLJAR Studio
MLJAR
$20 per monthThis desktop application integrates Jupyter Notebook and Python, allowing for a seamless one-click installation. It features engaging code snippets alongside an AI assistant that enhances coding efficiency, making it an ideal tool for data science endeavors. We have meticulously developed over 100 interactive code recipes tailored for your Data Science projects, which can identify available packages within your current environment. With a single click, you can install any required modules, streamlining your workflow significantly. Users can easily create and manipulate all variables present in their Python session, while these interactive recipes expedite the completion of tasks. The AI Assistant, equipped with knowledge of your active Python session, variables, and modules, is designed to address data challenges using the Python programming language. It offers support for various tasks, including plotting, data loading, data wrangling, and machine learning. If you encounter code issues, simply click the Fix button, and the AI assistant will analyze the problem and suggest a viable solution, making your coding experience smoother and more productive. Additionally, this innovative tool not only simplifies coding but also enhances your learning curve in data science. -
12
Llama 3.3
Meta
FreeThe newest version in the Llama series, Llama 3.3, represents a significant advancement in language models aimed at enhancing AI's capabilities in understanding and communication. It boasts improved contextual reasoning, superior language generation, and advanced fine-tuning features aimed at producing exceptionally accurate, human-like responses across a variety of uses. This iteration incorporates a more extensive training dataset, refined algorithms for deeper comprehension, and mitigated biases compared to earlier versions. Llama 3.3 stands out in applications including natural language understanding, creative writing, technical explanations, and multilingual interactions, making it a crucial asset for businesses, developers, and researchers alike. Additionally, its modular architecture facilitates customizable deployment in specific fields, ensuring it remains versatile and high-performing even in large-scale applications. With these enhancements, Llama 3.3 is poised to redefine the standards of AI language models. -
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ChatCPA
ChatCPA
$59/month ChatCPA is a practice question bank for the US CPA exam, built by a licensed CPA who passed scoring in the mid-70s, like most people who pass. The loop is Drill, Decode, Demonstrate. Drill 15,000+ original MCQs, written in AICPA style, filtered by section, topic, and subtopic. Decode with a full explanation on every question. Then Demonstrate: explain the concept back in your own words and an AI grader scores your explanation and shows a model answer. If you can teach it, you know it. If you can only recognize it, the exam will find out. CPA exam test bank with AI grading. Drill practice MCQs by topic, then explain answers in your own words and get scored on your explanation. Free 20-question sample, no credit card. Not included: video lectures, textbooks, or pass guarantees. This is a drilling tool. Use it alongside your review course or on its own. Pricing is flat and public: $59/month, $279 for six months, $499 lifetime. No per-section upsells. Try first: free 20-question sample at chatcpa.io with real questions and teach-back enabled. No credit card. 15,000+ original CPA exam practice MCQs with full explanations AI teach-back grading: explain answers in your own words and get scored Model answers written at beginner level for every teach-back Filter drills by section, topic, and subtopic Progress tracking by topic AI tutor for follow-up questions on any problem Free 20-question sample, no credit card Flat pricing, lifetime option, no per-section upsells -
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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. -
16
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. -
18
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. -
19
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. -
20
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. -
21
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. -
22
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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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. -
24
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.
