Alternatives to Holo2
Compare Holo2 alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Holo2 in 2026. Compare features, ratings, user reviews, pricing, and more from Holo2 competitors and alternatives in order to make an informed decision for your business.
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1
Laguna S 2.1
Poolside
Laguna S 2.1 is an open weight agentic coding model designed to pursue longer-horizon work and make effective use of reasoning. It uses a 118-billion-parameter Mixture-of-Experts architecture with 8 billion active parameters per token and supports a context window of up to one million tokens in both thinking and no-thinking modes. Its compact active size makes it suitable for complex work on local machines while remaining competitive with models many times larger on terminal, software-engineering, codebase-question-answering, and tool-use benchmarks. Laguna S 2.1 is built to keep working through difficult tasks with greater persistence, verification, and willingness to backtrack instead of declaring success too early. In demonstrated runs, it built and validated a browser rendering engine from an empty folder, optimized an agent harness for faster execution and substantially lower memory allocation, and completed extended mathematical research using the tools in its environment. -
2
Holo3
H Company
Holo3 is a state-of-the-art multimodal AI model developed by H Company, specifically designed to operate computers and execute tasks within graphical user interfaces (GUIs) across web, desktop, and mobile environments. Unlike traditional language models that generate text, Holo3 functions as a “computer-use” model: it takes screenshots of a system as input, interprets the visual interface, and outputs precise actions such as clicks, typing, and scrolling to complete real tasks step by step. Built on a Mixture-of-Experts architecture, it efficiently handles complex, multi-step workflows while reducing computational cost by activating only a subset of parameters per task. The model is engineered for real-world deployment and integrates into enterprise workflows through an agent-based platform that allows organizations to configure, deploy, and monitor automated processes end to end. -
3
Holo3.1
H Company
Holo3.1 is H Company’s family of fast and local computer-use agents, built to operate across web, desktop, and mobile environments while integrating more smoothly into different agent frameworks and deployment targets. Based on the Qwen family, Holo3.1 improves robustness across the environments where computer-use agents are actually deployed, addressing the distribution shifts that appear across mobile devices, alternative agent harnesses, and different execution frameworks. The release expands Holo3’s capabilities beyond browser and desktop control, with major gains in mobile automation, including AndroidWorld improvements from 67% to 79.3% for the 35B-A3B model and from 58% to 71% for the smaller 4B and 9B variants. Holo3.1 also introduces native support for function-calling protocols in addition to structured JSON outputs, helping teams deploy the model inside third-party agent stacks with near-parity between function-calling and native execution. -
4
Holo4
H Company
Holo4 is a family of generalist agentic AI models from H Company designed to operate software across graphical interfaces, code environments, MCP servers, APIs, desktop applications, the web, and mobile devices. The family includes a 27B dense model and a 35B-A3B Mixture-of-Experts model with 3B active parameters, both supporting a 256K context window. Unlike agents optimized around a single interface, Holo4 can click and type on screens, write and execute code, and call MCP or API tools depending on what a task requires. The models were trained with supervised fine-tuning and reinforcement learning on agentic workflows spanning desktop, web, MCP/API, mobile, coding, multimodal reasoning, and GUI grounding. Holo4 27B achieved 85.2% on OSWorld at a reported cost of $0.08 per task, while Holo4 35B-A3B scored 80.8% at $0.05 per task in H Company's evaluation.Starting Price: $0.40 per 1M tokens (input) -
5
Holo
Holo
Holo is an all-in-one AI marketing tool built to launch 10x more content, 75% faster. Drop in a website link and Holo learns the brand in minutes, capturing tone, style, creative vision, audience pain points, and buying triggers, then turns that Brand DNA into ads, emails, social posts, UGC-style videos, TikTok-ready videos, stories, reels, and full promotional campaigns. Instead of working across tools, templates, and tabs, Holo gives founders, creators, and marketers one AI for marketing, built to scale across core content areas; videos, ads, socials, and emails. The workflow is simple, input your URL, swipe through fresh ideas, edit and customize anything without design skills, then download, publish, and test the content. Holo delivers daily content ideas so users can fill out a content calendar months in advance, with formats such as mythbusters, features, us-vs-them, testimonials, best-sellers, media, negative hooks, FAQs, before-and-after posts, problem-solution posts, etc.Starting Price: $12 per month -
6
Surfer H
H Company
Surfer H from H Company is an autonomous web-agent platform built to understand and navigate user interfaces like a human by combining three modular models; a policy model that plans tasks, a localizer model that identifies UI elements visually, and a validator model that checks outcomes. The agent works purely through the browser interface with no special API hooks, enabling it to scroll, click, type, and complete real-web tasks such as booking hotels, comparing product deals, or extracting structured information. When paired with H Company’s open-weight vision-language models, Surfer H achieved state-of-the-art performance on the WebVoyager benchmark (92.2% accuracy at around $0.13 per task) and supports deployment locally, via Docker, or on cloud infrastructure. Use cases span web automation, QA testing without brittle scripts, data harvesting, and intelligent workflow agents that interact with the web directly as a human would.Starting Price: $0.13 per task -
7
Qwen2
Alibaba
Qwen2 is the large language model series developed by Qwen team, Alibaba Cloud. Qwen2 is a series of large language models developed by the Qwen team at Alibaba Cloud. It includes both base language models and instruction-tuned models, ranging from 0.5 billion to 72 billion parameters, and features both dense models and a Mixture-of-Experts model. The Qwen2 series is designed to surpass most previous open-weight models, including its predecessor Qwen1.5, and to compete with proprietary models across a broad spectrum of benchmarks in language understanding, generation, multilingual capabilities, coding, mathematics, and reasoning.Starting Price: Free -
8
VSI HoloMedicine
apoQlar
VSI HoloMedicine® by apoQlar is a software platform that leverages the Microsoft HoloLens 2 hardware to transform medical images, clinical workflows and medical education into a 3D mixed reality environment the world has never seen before. Go beyond the confines of a textbook with VSI’s digital library of real-world medical images, cases, and lectures in volumetric 3D mixed reality. Simplify structural relationships and anatomical comprehension for your students by offering segmentation tools. Experience real world human anatomy cases as well as complex pathology images like never before. Simplify structural relationships and anatomical comprehension for your students by offering segmentation tools. We take a holistic approach to innovating medicine and have reimagined effective clinical workflows in medical mixed reality. Our medical advisory board of nearly 30 specialized physicians across the globe drive our research & development to ensure clinical validation. -
9
Matplotlib
Matplotlib
Matplotlib is a comprehensive library for creating static, animated, and interactive visualizations in Python. Matplotlib makes easy things easy and hard things possible. A large number of third party packages extend and build on Matplotlib functionality, including several higher-level plotting interfaces (seaborn, HoloViews, ggplot, ...), and a projection and mapping toolkit (Cartopy).Starting Price: Free -
10
Qwen3.6-35B-A3B
Alibaba
Qwen3.5-35B-A3B is part of the Qwen3.5 “Medium” model series, designed as a highly efficient, multimodal foundation model that balances strong reasoning ability with practical deployment requirements. It uses a Mixture-of-Experts (MoE) architecture with 35 billion total parameters but activates only about 3 billion per token, allowing it to deliver performance comparable to much larger models while significantly reducing computational cost. The model integrates a hybrid attention mechanism that combines linear attention with standard attention layers, enabling efficient long-context processing and improved scalability for complex tasks. As a native vision-language model, it can process both text and visual inputs, supporting use cases such as multimodal reasoning, coding, and agent-based workflows. It is designed to function as a general-purpose “AI agent,” capable of planning, tool use, and structured problem solving rather than just conversational responses.Starting Price: Free -
11
Qwen3.5
Alibaba
Qwen3.5 is a next-generation open-weight multimodal large language model designed to power native vision-language agents. The flagship release, Qwen3.5-397B-A17B, combines a hybrid linear attention architecture with sparse mixture-of-experts, activating only 17 billion parameters per forward pass out of 397 billion total to maximize efficiency. It delivers strong benchmark performance across reasoning, coding, multilingual understanding, visual reasoning, and agent-based tasks. The model expands language support from 119 to 201 languages and dialects while introducing a 1M-token context window in its hosted version, Qwen3.5-Plus. Built for multimodal tasks, it processes text, images, and video with advanced spatial reasoning and tool integration. Qwen3.5 also incorporates scalable reinforcement learning environments to improve general agent capabilities. Designed for developers and enterprises, it enables efficient, tool-augmented, multimodal AI workflows.Starting Price: Free -
12
Lux
OpenAGI Foundation
Lux is a powerful computer-use AI platform that enables agents to operate software just like a human user—clicking, typing, navigating, and completing tasks across any interface. It offers three execution modes—Tasker, Actor, and Thinker—giving developers the ability to choose between step-by-step precision, near-instant task execution, or long-form reasoning for complex workflows. Lux can autonomously perform actions such as crawling Amazon data, running automated QA tests, or extracting insights from Nasdaq’s insider activity pages. The platform makes it possible to prototype and deploy real computer-use agents in as little as 20 minutes using developer-friendly SDKs and templates. Its agents are built to understand vague goals, execute long-running operations, and interact naturally with human-facing software instead of relying solely on APIs. Lux represents a new paradigm where AI goes beyond reasoning and content generation to directly operate computers at scale.Starting Price: Free -
13
Nemotron 3 Nano
NVIDIA
Nemotron 3 Nano is the smallest model in the NVIDIA Nemotron 3 family, built for agentic AI applications with strong reasoning, conversational ability, and cost-efficient inference. It is a hybrid Mamba-Transformer Mixture-of-Experts model with 3.2 billion active parameters, 3.6 billion including embeddings, and 31.6 billion total parameters. NVIDIA describes it as more accurate than the previous Nemotron 2 Nano while activating less than half of the parameters per forward pass, improving efficiency without sacrificing performance. The model is positioned as more accurate than GPT-OSS-20B and Qwen3-30B-A3B-Thinking-2507 on popular benchmarks across different categories. On an 8K input and 16K output setting using a single H200, it delivers inference throughput 3.3 times higher than Qwen3-30B-A3B and 2.2 times higher than GPT-OSS-20B. Nemotron 3 Nano supports context lengths up to 1 million tokens and is reported to outperform GPT-OSS-20B and Qwen3-30B-A3B-Instruct-2507. -
14
Spectar
Spectar
Spectar empowers construction companies by bringing actionable BIM data to the field with augmented reality. Our latest release, Spectar 2.0 unleashes the power of the HoloLens 2, with improved computing, powerful new features and tools, and superior user experience. Spectar customers are actively seeing an increase in productivity of up to 50% on jobsites. QC becomes faster, easier, and more comprehensive with the model at a 1:1 scale on the job site. Teams with Spectar are able to better communicate with a shared understanding of design intent. Spectar enables construction teams to identify issues faster and avoid costly rework by visualizing the BIM model at a 1:1 scale in the field. By visualizing the model on-site, install teams can access critical information and address potential clashes ahead of time, significantly reducing installation times. Spectar enables prefab teams to create and form materials to spec. -
15
Trimble Connect
Trimble MEP
Connect the right people to the right data at the right time. By giving everyone access to detailed project information, Trimble® Connect helps us all build better by making project information transparent, traceable and accessible. See 3D models with full-scale overlay in the real world with our HoloLens application. With mobile, desktop and web accessibility, stakeholders can access what they need, when they need it. Using our cloud-based collaboration platform, MEP contractors and engineers can coordinate, communicate and collaborate directly. Achieve predictable control by consolidating information across the design, build, and operate project phases. Trimble Connect is the glue between software and hardware products across the entire MEP workflow, connecting the different stages of a project and the countless contractors working on it.Starting Price: $10 per user per month -
16
Agent S
Simular
Agent S is an open-source agentic framework built to enable autonomous computer use through an Agent-Computer Interface (ACI). It allows AI agents to operate graphical user interfaces similarly to humans by perceiving screens, reasoning through objectives, and executing actions across macOS, Windows, and Linux systems. The latest release, Agent S3, achieves state-of-the-art results on the OSWorld benchmark and surpasses human-level performance in complex multi-step computer tasks. By combining powerful foundation models such as GPT-5 with grounding models like UI-TARS, the framework translates visual inputs into accurate executable commands. Agent S supports multiple deployment options, including CLI, SDK, and cloud environments. It integrates seamlessly with leading model providers such as OpenAI, Anthropic, Gemini, Azure, and Hugging Face endpoints. -
17
Qwen3-Coder-Next
Alibaba
Qwen3-Coder-Next is an open-weight language model specifically designed for coding agents and local development that delivers advanced coding reasoning, complex tool usage, and robust performance on long-horizon programming tasks with high efficiency, using a mixture-of-experts architecture that balances powerful capabilities with resource-friendly operation. It provides enhanced agentic coding abilities that help software developers, AI system builders, and automated coding workflows generate, debug, and reason about code with deep contextual understanding while recovering from execution errors, making it well-suited for autonomous coding agents and development-oriented applications. By achieving strong performance comparable to much larger parameter models while requiring fewer active parameters, Qwen3-Coder-Next enables cost-effective deployment for dynamic and complex programming workloads in research and production environments.Starting Price: Free -
18
Qwen2.5-VL
Alibaba
Qwen2.5-VL is the latest vision-language model from the Qwen series, representing a significant advancement over its predecessor, Qwen2-VL. This model excels in visual understanding, capable of recognizing a wide array of objects, including text, charts, icons, graphics, and layouts within images. It functions as a visual agent, capable of reasoning and dynamically directing tools, enabling applications such as computer and phone usage. Qwen2.5-VL can comprehend videos exceeding one hour in length and can pinpoint relevant segments within them. Additionally, it accurately localizes objects in images by generating bounding boxes or points and provides stable JSON outputs for coordinates and attributes. The model also supports structured outputs for data like scanned invoices, forms, and tables, benefiting sectors such as finance and commerce. Available in base and instruct versions across 3B, 7B, and 72B sizes, Qwen2.5-VL is accessible through platforms like Hugging Face and ModelScope.Starting Price: Free -
19
Kimi K2
Moonshot AI
Kimi K2 is a state-of-the-art open source large language model series built on a mixture-of-experts (MoE) architecture, featuring 1 trillion total parameters and 32 billion activated parameters for task-specific efficiency. Trained with the Muon optimizer on over 15.5 trillion tokens and stabilized by MuonClip’s attention-logit clamping, it delivers exceptional performance in frontier knowledge, reasoning, mathematics, coding, and general agentic workflows. Moonshot AI provides two variants, Kimi-K2-Base for research-level fine-tuning and Kimi-K2-Instruct pre-trained for immediate chat and tool-driven interactions, enabling both custom development and drop-in agentic capabilities. Benchmarks show it outperforms leading open source peers and rivals top proprietary models in coding tasks and complex task breakdowns, while its 128 K-token context length, tool-calling API compatibility, and support for industry-standard inference engines.Starting Price: Free -
20
Qwen3.6
Alibaba
Qwen3.6 is a large language model developed by Alibaba as part of its Qwen AI model family, designed for real-world applications and advanced reasoning tasks. It focuses on improving stability, usability, and performance compared to earlier versions. The model supports multimodal capabilities, allowing it to process and reason across text, images, and other data types. Qwen3.6 is particularly strong in coding and developer workflows, offering improved accuracy for complex programming tasks. It uses a mixture-of-experts architecture, enabling efficient performance while maintaining large-scale model capabilities. The model is designed to be deployable in production environments, including enterprise and cloud-based systems. It can be integrated into applications or run locally using open-weight variants. Overall, Qwen3.6 delivers a powerful, efficient, and versatile AI solution for modern use cases.Starting Price: Free -
21
GLM-5.1
Z.ai
GLM-5.1 is the latest iteration of Z.ai’s GLM series, designed as a frontier-level, agent-oriented AI model optimized for coding, reasoning, and long-horizon workflows. It builds on the GLM-5 architecture, which uses a Mixture-of-Experts (MoE) design to deliver high performance while keeping inference costs efficient, and is part of a broader push toward open-weight, developer-accessible models. A core focus of GLM-5.1 is enabling agentic behavior, meaning it can plan, execute, and iterate across multi-step tasks rather than simply responding to single prompts. It is specifically designed to handle complex workflows such as debugging code, navigating repositories, and executing chained operations with sustained context. Compared to earlier models, GLM-5.1 improves reliability in long interactions, maintaining coherence across extended sessions and reducing breakdowns in multi-step reasoning.Starting Price: Free -
22
Qwen3.5-Plus
Alibaba
Qwen3.5-Plus is a high-performance native vision-language model designed for efficient text generation, deep reasoning, and multimodal understanding. Built on a hybrid architecture that combines linear attention with a sparse mixture-of-experts design, it delivers strong performance while optimizing inference efficiency. The model supports text, image, and video inputs and produces text outputs, making it suitable for complex multimodal workflows. With a massive 1 million token context window and up to 64K output tokens, Qwen3.5-Plus enables long-form reasoning and large-scale document analysis. It includes advanced capabilities such as structured outputs, function calling, web search, and tool integration via the Responses API. The model supports prefix continuation, caching, batch processing, and fine-tuning for flexible deployment. Designed for developers and enterprises, Qwen3.5-Plus provides scalable, high-throughput AI performance with OpenAI-compatible API access.Starting Price: $0.4 per 1M tokens -
23
Open Computer Agent
Hugging Face
The Open Computer Agent is a browser-based AI assistant developed by Hugging Face that automates web interactions such as browsing, form-filling, and data retrieval. It leverages vision-language models like Qwen-VL to simulate mouse and keyboard actions, enabling tasks like booking tickets, checking store hours, and finding directions. Operating within a web browser, the agent can locate and interact with webpage elements using their image coordinates. As part of Hugging Face's smolagents project, it emphasizes flexibility and transparency, offering an open-source platform for developers to inspect, modify, and build upon for niche applications. While still in its early stages and facing challenges, the agent represents a new approach to AI as an active digital assistant, capable of performing online tasks without direct user input.Starting Price: Free -
24
Hy3
Tencent
Hy3 preview is Tencent Hy’s most intelligent model in the Hy series to date, built as a 295B-parameter Mixture-of-Experts model with 21B activated parameters, 3.8B MTP layer parameters, and support for up to a 256K token context window. As the first model trained on Tencent Hy’s rebuilt infrastructure, Hy3 preview is designed to improve real-world usability across complex reasoning, instruction following, context learning, coding, agent capabilities, and overall inference performance. It integrates both fast and slow thinking capabilities, allowing direct responses for simpler tasks and deeper reasoning for complex math, coding, and reasoning work. The model is built around well-rounded capabilities across long-context understanding, instruction following, tool use, and agent workflows, with evaluation focused not only on standard benchmarks but also on authentic business and development scenarios.Starting Price: Free -
25
Nemotron 3.5 Lightning
NVIDIA
NVIDIA Nemotron 3.5 Lightning is an open 30B-parameter mixture-of-experts model with 3B active parameters, designed for high-volume, low-latency execution in long-running and always-on AI agents. Built for the execution layer of agentic systems, it handles frequent tasks such as tool calls, output validation, routine commands, and subagent delegation while larger reasoning models focus on planning and orchestration. Its MoE architecture activates only a fraction of parameters for each token, combining the capacity of a larger model with lower compute requirements. The model is trained for popular agent harnesses and supports speculative decoding through multi-token prediction, DFlash, and DSpark to improve inference speed across different serving scenarios. It is available with BF16 and NVFP4 checkpoints and can run from local systems such as DGX Spark and GeForce RTX hardware to data center environments. -
26
Microsoft Mesh
Microsoft
Microsoft Mesh enables presence and shared experiences from anywhere – on any device – through mixed reality applications. Connect with new depth and dimension. Engage with eye contact, facial expressions, and gestures. Your personality shines as technology fades away. Digital intelligence comes to the real world. See, share, and collaborate on persistent 3D content. This common understanding ignites ideas, sparks creativity, and forms powerful bonds. Enjoy the freedom to access Mesh on HoloLens 2, VR headsets, mobile phones, tablets, or PCs – using any Mesh-enabled app. Project yourself as your most lifelike, photorealistic self in mixed reality to interact as if you’re there in person. Move through your world and get relevant, digital information when, and where, you need it. This fluidity accelerates decision-making and speeds problem-solving. -
27
HyperSkill
SimInsights Inc.
HyperSkill is an AI-powered, no-code XR platform that enables users to create, publish, and evaluate immersive VR training content without the need for programming skills. Designed for education, workforce training, and skill development, HyperSkill offers a drag-and-drop interface for customizing VR training simulations, allowing users to add interactive 3D assets, step-by-step instructions, highlights, and dialogue to design conversations. It supports a wide range of VR and AR devices, including mobile devices, high-end AR (HoloLens, Magic Leap), and VR headsets (HTC Vive, Oculus Quest, Rift), ensuring cross-platform compatibility. HyperSkill provides a library of over 300 pre-built simulations across various industries such as healthcare, manufacturing, education, and soft skills, facilitating rapid deployment of training programs.Starting Price: Free -
28
REFLEKT ONE
RE'FLEKT
Make work easier with step-by-step instructions, digital training guides and real-time data visualization. REFLEKT ONE is a modular Augmented Reality Platform for front-line workers including the AR Viewer application and our no-code content platform. With the AR Viewer your teams visualize critical information and IoT data on all major platforms and AR glasses. Workers are faced with complex products and processes every day. Outdated documentation and tools make their life even more complicated. Traditional manuals are history. Make information easy to consume to avoid mistakes and increase productivity. Visual step-by-step instructions displayed in the worker's field-of-view provide a friction-less experience. Service engineers get trained with the white-labeled augmented reality software available on iOS, Android, Windows, and Microsoft HoloLens. -
29
Qwen3.8-Flash-Next
Alibaba
Qwen3.8-Flash-Next is an open-weight multimodal Mixture-of-Experts model and an early preview of the architecture planned for Qwen4. It systematically upgrades attention, residual connections, embeddings, and optimization to improve capability, computational efficiency, model capacity, and training stability. Its hybrid architecture combines Gated DeltaNet, which efficiently compresses historical information, with Qwen Sparse Attention, which selects important context at the micro-block level to reduce attention and indexing costs on long sequences. Gated Residual widens the residual stream into four branches and dynamically controls information flow across layers, while N-gram Embedding adds large-scale local-pattern memory with very little extra per-token computation and can be offloaded to host memory. The model uses a 125B-parameter main network plus 51B N-gram embedding parameters, while activating only 6B parameters per token.Starting Price: $2 per 1M (input) -
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Qwen3.8-2.4T-A95B
Alibaba
Qwen3.8-2.4T-A95B is the largest open model in the Qwen3.8 family, bringing Qwen-Max-class capabilities to an open release. Built on the architectural foundation of Qwen3.5, it delivers substantial improvements across coding, professional work, research, and long-horizon agentic tasks, with a focus on carrying complex, multi-step work through to completion more reliably. The causal language model uses a mixture-of-experts architecture with 2.4 trillion total parameters and 95 billion activated parameters, including 512 experts with 10 routed and one shared expert active at a time. It supports a native context length of 262,144 tokens that can be extended to approximately 1.01 million tokens. Agent execution is strengthened through better autonomous planning and improved handling of environment feedback, while broader compatibility with popular agent harnesses and development tools simplifies integration into existing stacks. -
31
Qwen3-Coder
Qwen
Qwen3‑Coder is an agentic code model available in multiple sizes, led by the 480B‑parameter Mixture‑of‑Experts variant (35B active) that natively supports 256K‑token contexts (extendable to 1M) and achieves state‑of‑the‑art results comparable to Claude Sonnet 4. Pre‑training on 7.5T tokens (70 % code) and synthetic data cleaned via Qwen2.5‑Coder optimized both coding proficiency and general abilities, while post‑training employs large‑scale, execution‑driven reinforcement learning, scaling test‑case generation for diverse coding challenges, and long‑horizon RL across 20,000 parallel environments to excel on multi‑turn software‑engineering benchmarks like SWE‑Bench Verified without test‑time scaling. Alongside the model, the open source Qwen Code CLI (forked from Gemini Code) unleashes Qwen3‑Coder in agentic workflows with customized prompts, function calling protocols, and seamless integration with Node.js, OpenAI SDKs, and environment variables.Starting Price: Free -
32
Nemotron 3 Super
NVIDIA
Nemotron-3 Super is part of NVIDIA’s Nemotron 3 family of open models designed to enable advanced agentic AI systems that can reason, plan, and execute multi-step workflows across complex environments. The model introduces a hybrid Mamba-Transformer Mixture-of-Experts architecture that combines the efficiency of state-space Mamba layers with the contextual understanding of transformer attention, allowing it to process long sequences and complex reasoning tasks with high accuracy and throughput. This architecture activates only a subset of model parameters for each token, improving computational efficiency while maintaining strong reasoning capabilities and enabling scalable inference for large workloads. Nemotron-3 Super contains roughly 120 billion parameters with around 12 billion active during inference, accelerating multi-step reasoning and collaborative agent interactions across large contexts. -
33
HunyuanOCR
Tencent
Tencent Hunyuan is a large-scale, multimodal AI model family developed by Tencent that spans text, image, video, and 3D modalities, designed for general-purpose AI tasks like content generation, visual reasoning, and business automation. Its model lineup includes variants optimized for natural language understanding, multimodal vision-language comprehension (e.g., image & video understanding), text-to-image creation, video generation, and 3D content generation. Hunyuan models leverage a mixture-of-experts architecture and other innovations (like hybrid “mamba-transformer” designs) to deliver strong performance on reasoning, long-context understanding, cross-modal tasks, and efficient inference. For example, the vision-language model Hunyuan-Vision-1.5 supports “thinking-on-image”, enabling deep multimodal understanding and reasoning on images, video frames, diagrams, or spatial data. -
34
Cua
Cua
Cua is a computer-use agent platform that lets AI agents see screens, click buttons, type, and run code just like a human across macOS, Windows, Linux, browsers, and mobile environments. It provides cloud-based, sandboxed desktops where agents can automate real software workflows without relying on APIs. Built on open-source Cua agents, the platform enables developers to build, run, and scale computer-use agents with precision and reliability. Cua supports multi-step tasks, structured outputs, and human-in-the-loop recovery for complex automation. Agents operate in fully isolated environments to ensure safety and reproducibility. Cua is designed to make AI interaction with real applications practical and scalable.Starting Price: $10/month -
35
WakingApp
WakingApp
WakingApp has a proprietary AR platform with technologies to help enterprises across industries easily create cutting-edge AR experiences. The acquisition of WakingApp by Scope AR expands the company’s resources to more rapidly deliver new functionality to its WorkLink solution and push the boundaries of what’s possible in enterprise AR as the market continues to mature. WorkLink is the industry’s only industrial AR knowledge platform to provide real-time remote assistance and access to pre-built AR work instructions simultaneously in one application to allow workers to easily access the knowledge they need. With support for Microsoft HoloLens 2, WorkLink users can explore even more complex, hands-free use cases as a result of the device’s improved wearability, expanded field of view, and enhanced gesture control and eye tracking. Now, enterprise workers can perform longer maintenance, repair or manufacturing procedures and conduct industrial tasks that require more precise control.Starting Price: $55 per month -
36
Command A+
Cohere AI
Command A+ is Cohere’s fastest and most powerful language model yet, an open-source enterprise workhorse built for complex reasoning, multimodal and multilingual agentic tasks, and efficient private deployment. It is a sparse mixture-of-experts model with 218B total parameters and 25B active parameters, designed for high-performance agentic workflows with minimal compute overhead. Command A+ unifies capabilities from across the Command family into one scalable model, supporting text, image, reasoning, and tool use with a 128K input context, 64K max generation, and support for 48 languages. It is optimized for reasoning, agentic workflows, RAG, multilingual work, and multimodal document processing, with support for vLLM and Transformers. Compared with earlier Command A models, it improves enterprise workload performance across multimodal understanding, retrieval, long-horizon tasks, complex reasoning, coding, translation, and document understanding. -
37
AR Foundation
Unity
A framework purpose-built for augmented reality development that allows you to build rich experiences once, then deploy across multiple mobile and wearable AR devices. AR Foundation includes core features from ARKit, ARCore, Magic Leap, and HoloLens, as well as unique Unity features to build robust apps that are ready to ship to internal stakeholders or on any app store. This framework enables you to take advantage of all of these features in a unified workflow. AR Foundation lets you take currently unavailable features with you when you switch between AR platforms. If a feature is enabled on one platform but not another, we put hooks in so that it’s ready to go later. When the feature is enabled on the new platform, you can easily integrate it by updating your packages rather than having to completely rebuild your app from scratch. Take advantage of all the awesome features and workflows we’re building for Unity, from the Universal Render Pipeline to ECS.Starting Price: $399 per year -
38
MRTK-Unity
Microsoft
MRTK-Unity is a Microsoft-driven project that provides a set of components and features, used to accelerate cross-platform MR app development in Unity. Provides the cross-platform input system and building blocks for spatial interactions and UI. Enables rapid prototyping via in-editor simulation that allows you to see changes immediately. Operates as an extensible framework that provides developers the ability to swap out core components. A button control that supports various input methods, including HoloLens 2's articulated hand. Standard UI for manipulating objects in 3D space. Script for manipulating objects with one or two hands. 2D style plane which supports scrolling with articulated hand input. A script for making objects interactable with visual states and theme support. Various object positioning behaviors such as tag-along, body-lock, constant view size, and surface magnetism. Script for laying out an array of objects in a three-dimensional shape.Starting Price: Free -
39
Ivanti Neurons for MDM
Ivanti
Ivanti Neurons for Mobile Device Management (MDM) delivers unified mobile device management across the full spectrum of modern endpoints, iOS, iPadOS, Android, macOS, ChromeOS, and Windows, alongside immersive and rugged devices including Microsoft HoloLens, Oculus, and Zebra hardware, all from a unified solution. Purpose-built for the Everywhere Work environment, it helps ensure that only authorized users, devices, apps, and services can access corporate resources, validating security posture continuously rather than just at enrollment. Automated onboarding via Apple Business Manager, Google Zero-Touch Enrollment, and Windows Autopilot reduces manual provisioning overhead at scale. App distribution, policy configuration, containerization, and selective wipe capabilities give IT granular control over corporate data without intruding on user privacy. With flexible cloud or on-premises deployment, bring-your-own-device support, and native integration with Ivanti Mobile Threat Defense. -
40
DeepSeek-V2
DeepSeek
DeepSeek-V2 is a state-of-the-art Mixture-of-Experts (MoE) language model introduced by DeepSeek-AI, characterized by its economical training and efficient inference capabilities. With a total of 236 billion parameters, of which only 21 billion are active per token, it supports a context length of up to 128K tokens. DeepSeek-V2 employs innovative architectures like Multi-head Latent Attention (MLA) for efficient inference by compressing the Key-Value (KV) cache and DeepSeekMoE for cost-effective training through sparse computation. This model significantly outperforms its predecessor, DeepSeek 67B, by saving 42.5% in training costs, reducing the KV cache by 93.3%, and enhancing generation throughput by 5.76 times. Pretrained on an 8.1 trillion token corpus, DeepSeek-V2 excels in language understanding, coding, and reasoning tasks, making it a top-tier performer among open-source models.Starting Price: Free -
41
Qwen2.5-Max
Alibaba
Qwen2.5-Max is a large-scale Mixture-of-Experts (MoE) model developed by the Qwen team, pretrained on over 20 trillion tokens and further refined through Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF). In evaluations, it outperforms models like DeepSeek V3 in benchmarks such as Arena-Hard, LiveBench, LiveCodeBench, and GPQA-Diamond, while also demonstrating competitive results in other assessments, including MMLU-Pro. Qwen2.5-Max is accessible via API through Alibaba Cloud and can be explored interactively on Qwen Chat.Starting Price: Free -
42
Nemotron 3
NVIDIA
NVIDIA Nemotron 3 is a family of open large language models developed by NVIDIA to power advanced reasoning, conversational AI, and autonomous AI agents. The Nemotron 3 series includes three models designed for different scales of AI workloads while maintaining high efficiency and accuracy. These models focus on “agentic AI” capabilities, meaning they can perform multi-step reasoning, coordinate with tools, and operate as components within multi-agent systems used in automation, research, and enterprise applications. The architecture uses a hybrid mixture-of-experts (MoE) design combined with transformer-based techniques, allowing the model to activate only a subset of parameters for each task, which improves performance while reducing computational cost. Nemotron 3 models are built to deliver strong reasoning, conversational, and planning abilities while maintaining high throughput for large-scale deployment. -
43
ComputerX
ComputerX
ComputerX is a computer-use agent that does your computer work for you—from automation to web research to creating deliverables. Just type what you need in simple, natural language, and ComputerX turns your words into action. -
44
Mistral Small 4
Mistral AI
Mistral Small 4 is an advanced open-source AI model developed by Mistral AI that combines reasoning, coding, and multimodal capabilities into a single system. It unifies the strengths of previous models such as Magistral for reasoning, Pixtral for multimodal processing, and Devstral for agentic coding tasks. The model can handle both text and image inputs, allowing it to perform tasks ranging from conversational chat to visual analysis and document understanding. Built with a mixture-of-experts architecture, Mistral Small 4 delivers efficient performance while scaling to complex workloads. It also features a configurable reasoning parameter that allows users to switch between fast responses and deeper analytical outputs. With a large context window and optimized inference performance, the model supports long-form interactions and complex workflows.Starting Price: Free -
45
K2 Horizon
Institute of Foundation Models
K2 Horizon is a connected fleet of six open models spanning 375B-A23B, 36B-A4B, 32B, 7B, 3.7B, and 0.9B, designed to deliver strong performance across reasoning, mathematics, coding, agentic tasks, and general capabilities. The models share core architecture, vocabulary, training methodology, interfaces, evaluation infrastructure, and deployment tooling, making it easier to move between sizes and route workloads dynamically. The 375B-A23B model is the fleet’s most capable option for complex reasoning, software engineering, research, and long-horizon agentic work, while the 32B and 36B-A4B models target powerful local deployment. The 36B-A4B model introduces Mixture-of-Value Attention, combining sparse attention with Mixture-of-Experts layers to activate about 4 billion parameters per token while approaching the performance of the dense 32B model. -
46
Qwen-7B
Alibaba
Qwen-7B is the 7B-parameter version of the large language model series, Qwen (abbr. Tongyi Qianwen), proposed by Alibaba Cloud. Qwen-7B is a Transformer-based large language model, which is pretrained on a large volume of data, including web texts, books, codes, etc. Additionally, based on the pretrained Qwen-7B, we release Qwen-7B-Chat, a large-model-based AI assistant, which is trained with alignment techniques. The features of the Qwen-7B series include: Trained with high-quality pretraining data. We have pretrained Qwen-7B on a self-constructed large-scale high-quality dataset of over 2.2 trillion tokens. The dataset includes plain texts and codes, and it covers a wide range of domains, including general domain data and professional domain data. Strong performance. In comparison with the models of the similar model size, we outperform the competitors on a series of benchmark datasets, which evaluates natural language understanding, mathematics, coding, etc. And more.Starting Price: Free -
47
Ling 3.0 Flash
Ant Group
Ling 3.0 Flash is a next-generation efficient language model designed for long-horizon agent workflows, combining fast response, low activation, and stable tool use. It uses a Mixture-of-Experts architecture with 124 billion total parameters and 5.1 billion activated parameters per token, providing capability while keeping inference efficient. The model supports a native 256K context window that can be extended up to 1 million tokens, with reliable retrieval across information placed at the beginning, middle, or end of long contexts. Compared with the previous Flash model, Ling 3.0 Flash improves stability on extended tasks, tool-calling accuracy, instruction following, compatibility with agent harnesses, and coding performance. Its optimized spatial understanding can construct physical scene grids and reason about relative positions, while hybrid reasoning improves success rates across tasks of varying difficulty. -
48
MiMo-V2-Flash
Xiaomi Technology
MiMo-V2-Flash is an open weight large language model developed by Xiaomi based on a Mixture-of-Experts (MoE) architecture that blends high performance with inference efficiency. It has 309 billion total parameters but activates only 15 billion active parameters per inference, letting it balance reasoning quality and computational efficiency while supporting extremely long context handling, for tasks like long-document understanding, code generation, and multi-step agent workflows. It incorporates a hybrid attention mechanism that interleaves sliding-window and global attention layers to reduce memory usage and maintain long-range comprehension, and it uses a Multi-Token Prediction (MTP) design that accelerates inference by processing batches of tokens in parallel. MiMo-V2-Flash delivers very fast generation speeds (up to ~150 tokens/second) and is optimized for agentic applications requiring sustained reasoning and multi-turn interactions.Starting Price: Free -
49
Qwen3.8-27B
Alibaba
Qwen3.8-27B is a compact open-weights model in Alibaba’s Qwen3.8 family, aimed at developers and researchers who want strong local AI performance without using the full Max-scale model. Reports from Alibaba’s Qwen3.8 launch state that Qwen3.8-27B was planned for open-weight release alongside Qwen3.8-Max, expanding access for builders working on AI applications. The model is positioned for coding, research, professional workflows, and local deployment scenarios where a 27B model can be more practical than frontier-scale systems. Qwen3.8’s broader launch emphasizes software development, document processing, data analysis, and professional “cowork” use cases. Qwen3.8-27B is especially relevant for teams that need a capable open model for experimentation, coding agents, assistant workflows, and self-hosted inference. Built for practical deployment, Qwen3.8-27B gives developers a smaller Qwen3.8 option for building AI tools, testing agents, and running advanced language model workflows. -
50
North Mini Code
Cohere
North Mini Code is Cohere’s first agentic coding model for developers and the inaugural member of its next generation of powerful models. Small, efficient, and open-source, it is built for the sovereign developer ecosystem and designed to deliver strong software development performance without requiring extensive hardware. North Mini Code is a mixture-of-experts model with 30B total parameters and 3B active parameters, giving developers access to agentic coding capabilities in a compact and efficient form. The model is optimized for code generation, agentic software engineering, and terminal tasks, with a 256K total context length and up to 64K maximum generation. It is built for real-world developer workflows, including understanding and orchestrating sub-agents, mapping system architecture, running code reviews, and supporting coding agents that need to reason through complex software tasks.
