Find and compare the best Artificial Intelligence software for OpenClaw in 2026
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Use the comparison tool below to compare the top Artificial Intelligence software for OpenClaw on the market. You can filter results by user reviews, pricing, features, platform, region, support options, integrations, and more.
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Qwen3.6-Max-Preview
Alibaba
FreeQwen3.6-Max-Preview represents an advanced frontier language model aimed at enhancing intelligence, following instructions, and improving real-world agent functionalities within the Qwen ecosystem. This preview builds upon the Qwen3 series, showcasing enhanced world knowledge, refined alignment with instructions, and notable advancements in coding performance for agents, which allows the model to adeptly manage intricate, multi-step tasks and software engineering processes. It is meticulously designed for scenarios requiring advanced reasoning and execution, where the model goes beyond merely generating responses to actively interacting with tools, processing lengthy contexts, and facilitating structured problem-solving in various fields such as coding, research, and enterprise operations. The architecture continues to embody the Qwen commitment to developing large-scale, high-efficiency models that can effectively manage extensive context windows while providing reliable performance across multilingual and knowledge-intensive projects. Moreover, its capabilities promise to significantly enhance productivity and innovation in diverse applications. -
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Kimi K2.6
Moonshot AI
FreeKimi K2.6 is an advanced agentic AI model created by Moonshot AI, aiming to enhance practical implementation, programming, and complex reasoning compared to its predecessors, K2 and K2.5. This model is based on a Mixture-of-Experts framework and the multimodal, agent-centric principles of the Kimi series, merging language comprehension, coding capabilities, and tool utilization into one cohesive system that can plan and execute intricate workflows. It features enhanced reasoning skills and significantly better agent planning, enabling it to deconstruct tasks, synchronize various tools, and tackle multi-file or multi-step challenges with increased precision and effectiveness. Additionally, it provides robust tool-calling capabilities with a high degree of reliability, facilitating seamless integration with external platforms like web searches or APIs, and incorporates built-in validation systems to guarantee the accuracy of execution formats. Notably, Kimi K2.6 represents a significant leap forward in the realm of AI, setting new standards for the complexity and reliability of automated tasks. -
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Qwen3.7-Max
Alibaba
FreeQwen3.7-Max represents the latest advancement in Qwen's proprietary models, tailored for the agent era, and serves as a robust foundation for various applications, including code writing and debugging, office workflow automation, and maintaining extended autonomous browser sessions. This model achieves top-tier coding performance, demonstrating superior capabilities in software engineering, terminal operations, GUI interactions, web browsing, and the utilization of agentic tools. By enhancing the alignment between model intelligence and real-world agent execution, Qwen3.7-Max facilitates advanced planning, long-context reasoning, dependable function invocation, and the execution of multi-step tasks within intricate workflows. Furthermore, it bolsters multimodal and document-centric tasks through Qwen Studio, which enables chatbot interactions, comprehends images and videos, generates images, processes documents, creates presentations, offers coding support, conducts in-depth research, and enables web development. This comprehensive suite of features positions Qwen3.7-Max as a leading solution for diverse operational needs in the modern digital landscape. -
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Hugging Face
Hugging Face
$9 per monthHugging Face is an AI community platform that provides state-of-the-art machine learning models, datasets, and APIs to help developers build intelligent applications. The platform’s extensive repository includes models for text generation, image recognition, and other advanced machine learning tasks. Hugging Face’s open-source ecosystem, with tools like Transformers and Tokenizers, empowers both individuals and enterprises to build, train, and deploy machine learning solutions at scale. It offers integration with major frameworks like TensorFlow and PyTorch for streamlined model development. -
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Ollama
Ollama
FreeOllama stands out as a cutting-edge platform that prioritizes the delivery of AI-driven tools and services, aimed at facilitating user interaction and the development of AI-enhanced applications. It allows users to run AI models directly on their local machines. By providing a diverse array of solutions, such as natural language processing capabilities and customizable AI functionalities, Ollama enables developers, businesses, and organizations to seamlessly incorporate sophisticated machine learning technologies into their operations. With a strong focus on user-friendliness and accessibility, Ollama seeks to streamline the AI experience, making it an attractive choice for those eager to leverage the power of artificial intelligence in their initiatives. This commitment to innovation not only enhances productivity but also opens doors for creative applications across various industries. -
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Kimi
Moonshot AI
FreeKimi is a highly capable assistant equipped with an extensive "memory" that allows her to read lengthy novels of up to 200,000 words and browse the Internet simultaneously. With her ability to comprehend and analyze long documents, Kimi is invaluable for quickly summarizing reports such as financial analyses and research findings, thereby streamlining your reading and organizational tasks. When it comes to studying for exams or delving into new subjects, Kimi can efficiently summarize and clarify complex information from textbooks or academic papers. For those engaged in programming or tech-related tasks, Kimi offers support by reproducing code or suggesting technical solutions based on your input, whether it's code snippets or pseudocode from your documents. Proficient in Chinese and capable of managing multilingual content, Kimi enhances communication and understanding in international settings, making her a versatile tool for global collaboration. Additionally, Kimi Chat can engage you in dynamic conversations or even embody your favorite game characters, providing both entertainment and a way to unwind. Not only does Kimi assist with productivity, but she also brings a fun and interactive element to your daily routine. -
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FLUX.1
Black Forest Labs
FreeFLUX.1 represents a revolutionary suite of open-source text-to-image models created by Black Forest Labs, achieving new heights in AI-generated imagery with an impressive 12 billion parameters. This model outperforms established competitors such as Midjourney V6, DALL-E 3, and Stable Diffusion 3 Ultra, providing enhanced image quality, intricate details, high prompt fidelity, and adaptability across a variety of styles and scenes. The FLUX.1 suite is available in three distinct variants: Pro for high-end commercial applications, Dev tailored for non-commercial research with efficiency on par with Pro, and Schnell designed for quick personal and local development initiatives under an Apache 2.0 license. Notably, its pioneering use of flow matching alongside rotary positional embeddings facilitates both effective and high-quality image synthesis. As a result, FLUX.1 represents a significant leap forward in the realm of AI-driven visual creativity, showcasing the potential of advancements in machine learning technology. This model not only elevates the standard for image generation but also empowers creators to explore new artistic possibilities. -
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Qwen3
Alibaba
FreeQwen3 is a state-of-the-art large language model designed to revolutionize the way we interact with AI. Featuring both thinking and non-thinking modes, Qwen3 allows users to customize its response style, ensuring optimal performance for both complex reasoning tasks and quick inquiries. With the ability to support 119 languages, the model is suitable for international projects. The model's hybrid training approach, which involves over 36 trillion tokens, ensures accuracy across a variety of disciplines, from coding to STEM problems. Its integration with platforms such as Hugging Face, ModelScope, and Kaggle allows for easy adoption in both research and production environments. By enhancing multilingual support and incorporating advanced AI techniques, Qwen3 is designed to push the boundaries of AI-driven applications. -
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ByteRover
ByteRover
$19.99 per monthByteRover serves as an innovative memory enhancement layer tailored for AI coding agents, facilitating the creation, retrieval, and sharing of "vibe-coding" memories among various projects and teams. Crafted for a fluid AI-supported development environment, it seamlessly integrates into any AI IDE through the Memory Compatibility Protocol (MCP) extension, allowing agents to automatically save and retrieve contextual information without disrupting existing workflows. With features such as instantaneous IDE integration, automated memory saving and retrieval, user-friendly memory management tools (including options to create, edit, delete, and prioritize memories), and collaborative intelligence sharing to uphold uniform coding standards, ByteRover empowers developer teams, regardless of size, to boost their AI coding productivity. This approach not only reduces the need for repetitive training but also ensures the maintenance of a centralized and easily searchable memory repository. By installing the ByteRover extension in your IDE, you can quickly begin harnessing and utilizing agent memory across multiple projects in just a few seconds, leading to enhanced team collaboration and coding efficiency. -
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Qwen3-Coder
Qwen
FreeQwen3-Coder is a versatile coding model that comes in various sizes, prominently featuring the 480B-parameter Mixture-of-Experts version with 35B active parameters, which naturally accommodates 256K-token contexts that can be extended to 1M tokens. This model achieves impressive performance that rivals Claude Sonnet 4, having undergone pre-training on 7.5 trillion tokens, with 70% of that being code, and utilizing synthetic data refined through Qwen2.5-Coder to enhance both coding skills and overall capabilities. Furthermore, the model benefits from post-training techniques that leverage extensive, execution-guided reinforcement learning, which facilitates the generation of diverse test cases across 20,000 parallel environments, thereby excelling in multi-turn software engineering tasks such as SWE-Bench Verified without needing test-time scaling. In addition to the model itself, the open-source Qwen Code CLI, derived from Gemini Code, empowers users to deploy Qwen3-Coder in dynamic workflows with tailored prompts and function calling protocols, while also offering smooth integration with Node.js, OpenAI SDKs, and environment variables. This comprehensive ecosystem supports developers in optimizing their coding projects effectively and efficiently. -
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FLUX.1 Krea
Krea
FreeFLUX.1 Krea [dev] is a cutting-edge, open-source diffusion transformer with 12 billion parameters, developed through the collaboration of Krea and Black Forest Labs, aimed at providing exceptional aesthetic precision and photorealistic outputs while avoiding the common “AI look.” This model is fully integrated into the FLUX.1-dev ecosystem and is built upon a foundational model (flux-dev-raw) that possesses extensive world knowledge. It utilizes a two-phase post-training approach that includes supervised fine-tuning on a carefully selected combination of high-quality and synthetic samples, followed by reinforcement learning driven by human feedback based on preference data to shape its stylistic outputs. Through the innovative use of negative prompts during pre-training, along with custom loss functions designed for classifier-free guidance and specific preference labels, it demonstrates substantial enhancements in quality with fewer than one million examples, achieving these results without the need for elaborate prompts or additional LoRA modules. This approach not only elevates the model's output but also sets a new standard in the field of AI-driven visual generation. -
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Qwen3-Max
Alibaba
FreeQwen3-Max represents Alibaba's cutting-edge large language model, featuring a staggering trillion parameters aimed at enhancing capabilities in tasks that require agency, coding, reasoning, and managing lengthy contexts. This model is an evolution of the Qwen3 series, leveraging advancements in architecture, training methods, and inference techniques; it integrates both thinker and non-thinker modes, incorporates a unique “thinking budget” system, and allows for dynamic mode adjustments based on task complexity. Capable of handling exceptionally lengthy inputs, processing hundreds of thousands of tokens, it also supports tool invocation and demonstrates impressive results across various benchmarks, including coding, multi-step reasoning, and agent evaluations like Tau2-Bench. While the initial version prioritizes instruction adherence in a non-thinking mode, Alibaba is set to introduce reasoning functionalities that will facilitate autonomous agent operations in the future. In addition to its existing multilingual capabilities and extensive training on trillions of tokens, Qwen3-Max is accessible through API interfaces that align seamlessly with OpenAI-style functionalities, ensuring broad usability across applications. This comprehensive framework positions Qwen3-Max as a formidable player in the realm of advanced artificial intelligence language models. -
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GLM-4.6
Z.ai
FreeGLM-4.6 builds upon the foundations laid by its predecessor, showcasing enhanced reasoning, coding, and agent capabilities, resulting in notable advancements in inferential accuracy, improved tool usage during reasoning tasks, and a more seamless integration within agent frameworks. In comprehensive benchmark evaluations that assess reasoning, coding, and agent performance, GLM-4.6 surpasses GLM-4.5 and competes robustly against other models like DeepSeek-V3.2-Exp and Claude Sonnet 4, although it still lags behind Claude Sonnet 4.5 in terms of coding capabilities. Furthermore, when subjected to practical tests utilizing an extensive “CC-Bench” suite that includes tasks in front-end development, tool creation, data analysis, and algorithmic challenges, GLM-4.6 outperforms GLM-4.5 while nearing parity with Claude Sonnet 4, achieving victory in approximately 48.6% of direct comparisons and demonstrating around 15% improved token efficiency. This latest model is accessible through the Z.ai API, providing developers the flexibility to implement it as either an LLM backend or as the core of an agent within the platform's API ecosystem. In addition, its advancements could significantly enhance productivity in various application domains, making it an attractive option for developers looking to leverage cutting-edge AI technology. -
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Qwen3-VL
Alibaba
FreeQwen3-VL represents the latest addition to Alibaba Cloud's Qwen model lineup, integrating sophisticated text processing with exceptional visual and video analysis capabilities into a cohesive multimodal framework. This model accommodates diverse input types, including text, images, and videos, and it is adept at managing lengthy and intertwined contexts, supporting up to 256 K tokens with potential for further expansion. With significant enhancements in spatial reasoning, visual understanding, and multimodal reasoning, Qwen3-VL's architecture features several groundbreaking innovations like Interleaved-MRoPE for reliable spatio-temporal positional encoding, DeepStack to utilize multi-level features from its Vision Transformer backbone for improved image-text correlation, and text–timestamp alignment for accurate reasoning of video content and time-related events. These advancements empower Qwen3-VL to analyze intricate scenes, track fluid video narratives, and interpret visual compositions with a high degree of sophistication. The model's capabilities mark a notable leap forward in the field of multimodal AI applications, showcasing its potential for a wide array of practical uses. -
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GLM-4.7
Z.ai
FreeGLM-4.7 is a next-generation AI model built to serve as a powerful coding and reasoning partner. It improves significantly on its predecessor across software engineering, multilingual coding, and terminal interaction benchmarks. GLM-4.7 introduces enhanced agentic behavior by thinking before tool use or execution, improving reliability in long and complex tasks. The model demonstrates strong performance in real-world coding environments and popular coding agents. GLM-4.7 also advances visual and frontend generation, producing modern UI designs and well-structured presentation slides. Its improved tool-use capabilities allow it to browse, analyze, and interact with external systems more effectively. Mathematical and logical reasoning have been strengthened through higher benchmark performance on challenging exams. The model supports flexible reasoning modes, allowing users to trade latency for accuracy. GLM-4.7 can be accessed via Z.ai, OpenRouter, and agent-based coding tools. It is designed for developers who need high performance without excessive cost. -
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MiniMax-M2.1
MiniMax
FreeMiniMax-M2.1 is a state-of-the-art open-source AI model built specifically for agent-based development and real-world automation. It focuses on delivering strong performance in coding, tool calling, and long-term task execution. Unlike closed models, MiniMax-M2.1 is fully transparent and can be deployed locally or integrated through APIs. The model excels in multilingual software engineering tasks and complex workflow automation. It demonstrates strong generalization across different agent frameworks and development environments. MiniMax-M2.1 supports advanced use cases such as autonomous coding, application building, and office task automation. Benchmarks show significant improvements over previous MiniMax versions. The model balances high reasoning ability with stability and control. Developers can fine-tune or extend it for specialized agent workflows. MiniMax-M2.1 empowers teams to build reliable AI agents without vendor lock-in. -
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Qwen3-TTS
Alibaba
FreeQwen3-TTS represents an innovative collection of advanced text-to-speech models created by the Qwen team at Alibaba Cloud, released under the Apache-2.0 license, which delivers stable, expressive, and real-time speech output with functionalities like voice cloning, voice design, and precise control over prosody and acoustic features. This suite supports ten prominent languages—Chinese, English, Japanese, Korean, German, French, Russian, Portuguese, Spanish, and Italian—along with various dialect-specific voice profiles, enabling adaptive management of tone, speech rate, and emotional delivery tailored to text semantics and user instructions. The architecture of Qwen3-TTS incorporates efficient tokenization and a dual-track design, facilitating ultra-low-latency streaming synthesis, with the first audio packet generated in approximately 97 milliseconds, making it ideal for interactive and real-time applications. Additionally, the range of models available offers diverse capabilities, such as rapid three-second voice cloning, customization of voice timbres, and voice design based on given instructions, ensuring versatility for users in many different scenarios. This flexibility in design and performance highlights the model's potential for a wide array of applications in both commercial and personal contexts. -
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Kimi Code CLI
Moonshot AI
FreeKimi Code CLI serves as an AI-driven command-line tool designed to aid developers in software creation and terminal tasks by interpreting and altering code, executing shell commands, retrieving web content, autonomously strategizing and modifying actions during processes, and offering an interactive shell environment where users can articulate their requirements in everyday language or switch to command mode for direct input; it seamlessly integrates with IDEs and local agent clients through the Agent Client Protocol, enhancing workflows and streamlining activities like code writing, bug fixing, project exploration, addressing architectural queries, and automating batch processes or build and test scripts. The installation process involves running a script that sets up the essential tool manager before downloading the Kimi CLI package, after which users can confirm installation with a version check and proceed to configure an API source for optimal functionality. Additionally, the Kimi Code CLI not only enhances productivity but also fosters a more intuitive interaction between developers and their coding environment. -
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happycapy
happycapy
$20/month happycapy serves as an agent-native AI platform that transforms your web browser into a robust "agent computer," allowing developers and users to launch and operate autonomous AI agents around the clock without relying on conventional server setups. This innovation enables the delegation of tasks to numerous large language models (LLMs) and AI services, including Claude Code, all within a secure, sandboxed environment. By facilitating the simultaneous operation of multiple AI agents, happycapy effectively manages coding, automation, data processing, and custom workflows, providing teams with a cohesive interface for orchestrating, scaling, and monitoring agent-related activities. The platform prioritizes flexibility and developer autonomy through a private sandbox, where agents can perform tasks, engage with code and data, and collaborate on intricate projects while overseeing state, logs, and outputs from various AI services. Additionally, happycapy streamlines the development and upkeep of AI-driven applications by simplifying the complexities associated with infrastructure and model management. This makes it easier for teams to harness the full potential of AI technology in their workflows. -
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Qwen3-Coder-Next
Alibaba
FreeQwen3-Coder-Next is a language model with open weights, crafted for coding agents and local development, which excels in advanced coding reasoning, adept tool usage, and effective handling of long-term programming challenges with remarkable efficiency, utilizing a mixture-of-experts framework that harmonizes robust capabilities with a resource-efficient approach. This model enhances the coding prowess of software developers, AI system architects, and automated coding processes, allowing them to generate, debug, and comprehend code with a profound contextual grasp while adeptly recovering from execution errors, rendering it ideal for autonomous coding agents and applications focused on development. Furthermore, Qwen3-Coder-Next achieves impressive performance on par with larger parameter models, but does so while consuming fewer active parameters, thus facilitating economical deployment for intricate and evolving programming tasks in both research and production settings, ultimately contributing to a more streamlined development process. -
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MiniMax M2.5
MiniMax
FreeMiniMax M2.5 is a next-generation foundation model built to power complex, economically valuable tasks with speed and cost efficiency. Trained using large-scale reinforcement learning across hundreds of thousands of real-world task environments, it excels in coding, tool use, search, and professional office workflows. In programming benchmarks such as SWE-Bench Verified and Multi-SWE-Bench, M2.5 reaches state-of-the-art levels while demonstrating improved multilingual coding performance. The model exhibits architect-level reasoning, planning system structure and feature decomposition before writing code. With throughput speeds of up to 100 tokens per second, it completes complex evaluations significantly faster than earlier versions. Reinforcement learning optimizations enable more precise search rounds and fewer reasoning steps, improving overall efficiency. M2.5 is available in two variants—standard and Lightning—offering identical capabilities with different speed configurations. Pricing is designed to be dramatically lower than competing frontier models, reducing cost barriers for large-scale agent deployment. Integrated into MiniMax Agent, the model supports advanced office skills including Word formatting, Excel financial modeling, and PowerPoint editing. By combining high performance, efficiency, and affordability, MiniMax M2.5 aims to make agent-powered productivity accessible at scale. -
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Atomic Bot
Atomic Bot
FreeAtomic Bot serves as a straightforward AI assistant app that harnesses the power of the OpenClaw autonomous agent framework within an easy-to-navigate interface, enabling users to automate various digital tasks without the need for complicated configurations. This application can operate either locally on your device or in the cloud utilizing your own LLM API keys, thereby granting users full control and safeguarding their data privacy. Additionally, it accommodates several AI models, including Claude, GPT, and Gemini, allowing you to select the engine that best aligns with your workflow requirements. Atomic Bot features persistent memory to retain preferences and tasks, adapts to your working habits over time, and can perform web-based tasks by navigating websites, executing processes, completing forms, and gathering information directly from chats. Furthermore, it is capable of automating recurring and scheduled tasks, keeping an eye on important matters, organizing files, and connecting with various everyday tools to enhance professional productivity. With its intuitive design and robust functionality, Atomic Bot not only simplifies task management but also elevates your overall efficiency in both personal and professional settings. -
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DeepSeek-V4
DeepSeek
FreeDeepSeek-V4 is an advanced open-source large language model engineered for efficient long-context processing and high-level reasoning tasks. Supporting a massive one million token context window, it enables developers to build applications that handle extensive data and complex workflows without fragmentation. The model is available in two versions: V4-Pro for maximum reasoning power and V4-Flash for faster, cost-efficient performance. DeepSeek-V4-Pro delivers top-tier results in coding, mathematics, and knowledge benchmarks, rivaling leading proprietary models. Its architecture incorporates innovative attention techniques that significantly improve efficiency while maintaining strong performance. The model is optimized for agent-based workflows, allowing seamless integration with tools and automation systems. It also supports dual reasoning modes, enabling users to switch between quick responses and deeper analytical outputs. DeepSeek-V4 is fully open-source, providing flexibility for customization and deployment across various environments. Overall, it offers a powerful and scalable solution for modern AI development. -
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AGBCLOUD
AGBCLOUD
FreeAGBCLOUD is a cloud-based sandbox platform designed for AI that offers developers and organizations secure and isolated environments to create and manage autonomous software agents. This platform provides agents with fully-equipped cloud development environments that facilitate multilingual code generation, compilation, and debugging through easily accessible browser sandboxes. By allowing advanced functionalities such as web browsing, computer interactions, and data analysis, AGBCLOUD ensures that AI systems can engage with files, applications, and the internet safely within a controlled space. Furthermore, it incorporates plug-and-play MCP tools alongside LLM-driven analytics to convert raw data into meaningful insights and dynamic applications. The sandbox architecture supports cross-platform capabilities, enabling agents to transition effortlessly between coding, browsing, and system-level tasks, all while upholding stringent security and isolation measures. This versatility opens up new possibilities for developers seeking to enhance their AI solutions. -
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Qwen3.5
Alibaba
FreeQwen3.5 represents a major advancement in open-weight multimodal AI models, engineered to function as a native vision-language agent system. Its flagship model, Qwen3.5-397B-A17B, leverages a hybrid architecture that fuses Gated DeltaNet linear attention with a high-sparsity mixture-of-experts framework, allowing only 17 billion parameters to activate during inference for improved speed and cost efficiency. Despite its sparse activation, the full 397-billion-parameter model achieves competitive performance across reasoning, coding, multilingual benchmarks, and complex agent evaluations. The hosted Qwen3.5-Plus version supports a one-million-token context window and includes built-in tool use for search, code interpretation, and adaptive reasoning. The model significantly expands multilingual coverage to 201 languages and dialects while improving encoding efficiency with a larger vocabulary. Native multimodal training enables strong performance in image understanding, video processing, document analysis, and spatial reasoning tasks. Its infrastructure includes FP8 precision pipelines and heterogeneous parallelism to boost throughput and reduce memory consumption. Reinforcement learning at scale enhances multi-step planning and general agent behavior across text and multimodal environments. Overall, Qwen3.5 positions itself as a high-efficiency foundation for autonomous digital agents capable of reasoning, searching, coding, and interacting with complex environments.
