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vision · Ollama
Search for models on Ollama.
  • qwen3-vl

    The most powerful vision-language model in the Qwen model family to date.

    vision tools thinking 2b 4b 8b 30b 32b 235b

    5.1M  Pulls 57  Tags Updated  9 months ago

  • deepseek-ocr

    DeepSeek-OCR is a vision-language model that can perform token-efficient OCR.

    vision 3b

    511.4K  Pulls 3  Tags Updated  8 months ago

  • llava

    🌋 LLaVA is a novel end-to-end trained large multimodal model that combines a vision encoder and Vicuna for general-purpose visual and language understanding. Updated to version 1.6.

    vision 7b 13b 34b

    14.6M  Pulls 98  Tags Updated  2 years ago

  • qwen2.5vl

    Flagship vision-language model of Qwen and also a significant leap from the previous Qwen2-VL.

    vision 3b 7b 32b 72b

    4.1M  Pulls 17  Tags Updated  1 year ago

  • llama3.2-vision

    Llama 3.2 Vision is a collection of instruction-tuned image reasoning generative models in 11B and 90B sizes.

    vision 11b 90b

    5M  Pulls 9  Tags Updated  1 year ago

  • minicpm-v

    A series of multimodal LLMs (MLLMs) designed for vision-language understanding.

    vision 8b

    5.4M  Pulls 17  Tags Updated  1 year ago

  • granite3.2-vision

    A compact and efficient vision-language model, specifically designed for visual document understanding, enabling automated content extraction from tables, charts, infographics, plots, diagrams, and more.

    vision tools 2b

    971.3K  Pulls 5  Tags Updated  1 year ago

  • mistral-small3.1

    Building upon Mistral Small 3, Mistral Small 3.1 (2503) adds state-of-the-art vision understanding and enhances long context capabilities up to 128k tokens without compromising text performance.

    vision tools 24b

    777K  Pulls 5  Tags Updated  1 year ago

  • moondream

    moondream2 is a small vision language model designed to run efficiently on edge devices.

    vision 1.8b

    1.5M  Pulls 18  Tags Updated  2 years ago

  • medgemma

    MedGemma is a collection of Gemma 3 variants that are trained for performance on medical text and image comprehension.

    vision 4b 27b

    266.1K  Pulls 9  Tags Updated  3 months ago

  • VisionVTAI/Aria-sama

    tools

    29  Pulls 1  Tag Updated  11 months ago

  • openchat

    A family of open-source models trained on a wide variety of data, surpassing ChatGPT on various benchmarks. Updated to version 3.5-0106.

    7b

    1.3M  Pulls 50  Tags Updated  2 years ago

  • edtorre/muse-glimmer-agent

    a 27.9B vision-language model tuned for agentic workflows.

    vision

    1  Pull 1  Tag Updated  15 hours ago

  • tinyrick/Qwen3.6-27B-Fable-Fusion-711-Uncensored-Heretic-NM-DAU-NEO-MAX-MTP-Vision

    vision

    1,813  Pulls 1  Tag Updated  1 week ago

  • numind/nuextract3

    NuExtract3 is a 4B vision-language reasoning model by NuMind for local document understanding. Turn text and document images into structured JSON or clean Markdown with Ollama, with support for multilingual documents, OCR, and template generation.

    vision tools thinking

    787  Pulls 4  Tags Updated  3 weeks ago

  • kenevo/DeepSeek-V4-Flash-UD-Q4_K_XL

    To run DeepSeek-V4-Flash in full precision lossless, run Q4 (UD-Q4_K_XL), It is 155GB. vision tools thinking

    533  Pulls 1  Tag Updated  2 weeks ago

  • NJIR/njir.gen-2

    Next-Gen Sovereign AI Ecosystem - 7 specialized models for Coding, Vision, Reasoning, Edge & RAG. 131K context, 11 Stop Tokens. Native with OpenClaw, VSCode, Cursor, LangChain & 12+ platforms. Forged by NJIRLAH.

    vision embedding tools thinking

    2.3M  Pulls 7  Tags Updated  2 months ago

  • 4skl/gemma4-e4b-mtp

    Multimodal 4.5B Gemma 4 with Unsloth Dynamic QAT & MTP (5.3GB). Features near-lossless vision, audio, text reasoning, an active 4-token speculative window, and an expanded 64K context size. Best for edge execution on systems with 8GB to 16GB RAM.

    vision tools thinking

    592  Pulls 1  Tag Updated  3 weeks ago

  • 4skl/gemma4-e2b-mtp

    Ultra-fast multimodal 2.3B Gemma 4 for on-device edge AI (3.7GB). Adds native vision/audio parsing to Unsloth Dynamic QAT with a 2-token MTP pipeline and a mobile-safe 32K context window. Perfect for smartphones and laptops sharing 8GB of total RAM.

    vision tools thinking

    475  Pulls 1  Tag Updated  3 weeks ago

  • byczech/qwen3.6-mmproj-16G-UD-IQ3_S

    Qwen 3.6 35B multimodal model with vision support, quantized to IQ3_S and optimized to fit within 16 GB VRAM with Q4_0 KV cache. Supports very large context windows, with the practical maximum depending on the Ollama version, GPU and backend.

    vision tools thinking 35b

    423  Pulls 1  Tag Updated  3 weeks ago

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