Compare the Top Multimodal Models that integrate with Ollama as of August 2026

This a list of Multimodal Models that integrate with Ollama. Use the filters on the left to add additional filters for products that have integrations with Ollama. View the products that work with Ollama in the table below.

What are Multimodal Models for Ollama?

Multimodal models are artificial intelligence models capable of understanding, processing, and generating multiple types of data—including text, images, audio, video, code, and other structured or unstructured inputs—within a single unified system. These models combine information across modalities to perform tasks such as visual question answering, image generation, speech recognition, video understanding, document analysis, code generation, and conversational AI. Many multimodal models support advanced capabilities such as tool use, reasoning, AI agents, and long-context processing, enabling more natural and context-aware interactions. They are commonly available through APIs, cloud AI platforms, and open-source frameworks for use in enterprise applications, creative workflows, robotics, healthcare, education, and software development. By integrating multiple forms of information into a single model, multimodal models enable more capable, flexible, and human-like AI systems. Compare and read user reviews of the best Multimodal Models for Ollama currently available using the table below. This list is updated regularly.

  • 1
    Qwen3.8-Max
    Qwen3.8-Max is Qwen’s most capable model to date, built as a Max-class AI model for coding, work, research, long-horizon tasks, and multimodal agents. It scales to 2.4 trillion parameters with 95 billion active parameters and is available through QwenCloud. The model is designed to complete complex, open-ended tasks end to end with greater reliability and minimal human involvement. Qwen3.8-Max supports autonomous coding workflows, agentic development, research reproduction, visual reasoning, document understanding, video analysis, and real-world productivity tasks. It can integrate with popular agent frameworks and coding assistants, including Claude Code, Codex, Qoder CLI, Qwen Code, and OpenClaw. Built for developers, researchers, enterprises, and AI agent builders, Qwen3.8-Max helps teams automate sophisticated work across code, documents, tools, interfaces, and multimodal content.
    Starting Price: $2 per 1M (input)
  • 2
    MiniMax M3

    MiniMax M3

    MiniMax

    MiniMax M3 is an open-weight multimodal AI model designed for coding, agentic workflows, long-context reasoning, and complex automation tasks. The model combines frontier-level coding performance, native multimodal understanding, and a context window of up to 1 million tokens. MiniMax M3 uses MiniMax Sparse Attention to improve long-context efficiency while reducing compute requirements for large-scale inputs. It supports text, image, and video understanding, making it useful for workflows that combine code, documents, visual references, and tool-driven tasks. The model is built for repository-scale reasoning, software engineering, autonomous task execution, tool calling, and multi-step agent workflows. MiniMax M3 helps developers, AI teams, and enterprises build capable agents that can reason across large contexts and work with multimodal information.
    Starting Price: Free
  • 3
    Mistral AI

    Mistral AI

    Mistral AI

    Mistral AI is a pioneering artificial intelligence startup specializing in open-source generative AI. The company offers a range of customizable, enterprise-grade AI solutions deployable across various platforms, including on-premises, cloud, edge, and devices. Flagship products include "Le Chat," a multilingual AI assistant designed to enhance productivity in both personal and professional contexts, and "La Plateforme," a developer platform that enables the creation and deployment of AI-powered applications. Committed to transparency and innovation, Mistral AI positions itself as a leading independent AI lab, contributing significantly to open-source AI and policy development.
    Starting Price: Free
  • 4
    Qwen

    Qwen

    Alibaba

    Qwen is a powerful, free AI assistant built on the advanced Qwen model series, designed to help anyone with creativity, research, problem-solving, and everyday tasks. While Qwen Chat is the main interface for most users, Qwen itself powers a broad range of intelligent capabilities including image generation, deep research, website creation, advanced reasoning, and context-aware search. Its multimodal intelligence enables Qwen to understand and process text, images, audio, and video simultaneously for richer insights. Qwen is available on web, desktop, and mobile, ensuring seamless access across all devices. For developers, the Qwen API provides OpenAI-compatible endpoints, making integration simple and allowing Qwen’s intelligence to power apps, services, and automation. Whether you're chatting through Qwen Chat or building with the Qwen API, Qwen delivers fast, flexible, and highly capable AI support.
    Starting Price: Free
  • 5
    Kimi K2.5

    Kimi K2.5

    Moonshot AI

    Kimi K2.5 is a next-generation multimodal AI model designed for advanced reasoning, coding, and visual understanding tasks. It features a native multimodal architecture that supports both text and visual inputs, enabling image and video comprehension alongside natural language processing. Kimi K2.5 delivers open-source state-of-the-art performance in agent workflows, software development, and general intelligence tasks. The model offers ultra-long context support with a 256K token window, making it suitable for large documents and complex conversations. It includes long-thinking capabilities that allow multi-step reasoning and tool invocation for solving challenging problems. Kimi K2.5 is fully compatible with the OpenAI API format, allowing developers to switch seamlessly with minimal changes. With strong performance, flexibility, and developer-focused tooling, Kimi K2.5 is built for production-grade AI applications.
    Starting Price: Free
  • 6
    Kimi K2.6

    Kimi K2.6

    Moonshot AI

    Kimi K2.6 is a next-generation agentic AI model developed by Moonshot AI, designed to push forward real-world execution, coding, and multi-step reasoning beyond earlier K2 and K2.5 versions. It builds on a Mixture-of-Experts architecture and the multimodal, agent-first foundation of the Kimi series, combining language understanding, coding, and tool use into a single system capable of planning and executing complex workflows. It introduces deeper reasoning capabilities and significantly improved agent planning, allowing it to break down tasks, coordinate tools, and handle multi-file or multi-step problems with greater accuracy and efficiency. It supports advanced tool calling with high reliability, enabling integration with external systems such as web search or APIs, and includes built-in validation mechanisms to ensure correct execution formats.
    Starting Price: Free
  • 7
    Qwen3.5

    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
  • 8
    Gemma 3n

    Gemma 3n

    Google DeepMind

    Gemma 3n is our state-of-the-art open multimodal model, engineered for on-device performance and efficiency. Made for responsive, low-footprint local inference, Gemma 3n empowers a new wave of intelligent, on-the-go applications. It analyzes and responds to combined images and text, with video and audio coming soon. Build intelligent, interactive features that put user privacy first and work reliably offline. Mobile-first architecture, with a significantly reduced memory footprint. Co-designed by Google's mobile hardware teams and industry leaders. 4B active memory footprint with the ability to create submodels for quality-latency tradeoffs. Gemma 3n is our first open model built on this groundbreaking, shared architecture, allowing developers to begin experimenting with this technology today in an early preview.
  • 9
    Qwen3.7-Plus
    Qwen3.7-Plus is a multimodal agent model that unifies vision and language into a single, versatile agent foundation. Building on Qwen3.7’s agentic intelligence, it extends Qwen’s capabilities into visual understanding, visual reasoning, grounded interaction, and multimodal tool use, enabling agents to perceive, analyze, and act across text, images, documents, screens, and complex real-world contexts. It is designed for tasks that require more than static question answering, including visual search, document comprehension, chart and table analysis, screen understanding, GUI interaction, image-grounded reasoning, and agent workflows that combine perception with planning and execution. Qwen3.7-Plus strengthens the connection between language reasoning and visual evidence, allowing users to ask questions about images, interpret dense multimodal inputs, extract structured information, and generate responses that reflect both context and visual details.
  • 10
    Qwen3.8-27B
    Qwen3.8-27B is an announced 27-billion-parameter model in Alibaba’s Qwen3.8 family, positioned as the compact open-weight counterpart to the much larger Qwen3.8-Max. Qwen introduced the broader Qwen3.8 generation as a new frontier model family focused on coding, agentic work, multimodal understanding, and long-running autonomous tasks. The 27B release is intended to bring that generation to a size that is far more practical for local deployment, experimentation, fine-tuning, and integration into developer workflows. Qwen has confirmed that Qwen3.8-27B will be released with open weights, extending the company’s line of downloadable mid-sized models for users who want direct control over inference and deployment. At the time of announcement, Qwen had not yet published the model card, benchmark table, architecture details, context length, quantization options, or complete deployment guidance for the 27B checkpoint.
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