Ollama vision models list.
Search for Vision models on Ollama.
Ollama vision models list Llama 3. The tag is used to identify a specific version. 2 instruction-tuned text only models are optimized for multilingual dialogue use cases, including agentic retrieval and summarization tasks. All durations are returned in nanoseconds. Building upon Mistral Small 3, Mistral Small 3. 7b 4B parameter model. 2-vision. 6B parameter model. Feb 2, 2024 路 These models are available in three parameter sizes. Model names follow a model:tag format, where model can have an optional namespace such as example/model. Models. Updated to version 1. 6b 1. ollama run qwen3:8b 14B parameter model. 0. ollama run qwen3:30b-a3b. 9K Pulls 6 Tags Updated 5 months ago Jan 13, 2025 路 Note: this model requires Ollama 0. Some examples are orca-mini:3b-q8_0 and llama3:70b. These models are on par with or better than equivalently sized fully open models, and competitive with open-weight models such as Llama 3. ollama run qwen3:4b 8B parameter model. To use a vision model with ollama run, reference . embedding 30m 278m 54. It tops the leaderboard among open-source models and rivals the most advanced closed-source models globally. 9K Pulls 6 Tags Updated 5 months ago granite3. 2 Vision is a collection of instruction-tuned image reasoning generative models in 11B and 90B sizes. 1 (2503) adds state-of-the-art vision understanding and enhances long context capabilities up to 128k tokens without compromising text performance. The tag is optional and, if not provided, will default to latest. # List all models (all variants) ollama-models -a # Find all llama models ollama-models -n llama # Find all vision-capable models ollama-models -c vision # Find all models with 7 billion parameters or less ollama-models -s -7 # Find models between 4 and 28 billion parameters (size range) ollama-models -s +4 -s -28 # Find top 5 most popular olmo2. vision 7b 13b 34b Sep 25, 2024 路 The Meta Llama 3. ollama run qwen3:32b 30B mixture-of-experts model with 3B active parameters. 7B parameter model. ollama run qwen3:1. 馃寢 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. 6. 5 or later. The Llama 4 model collection also supports the ability to leverage the outputs of its models to improve other models including synthetic data generation and distillation. The IBM Granite Embedding 30M and 278M models models are text-only dense biencoder embedding models, with 30M available in English only and 278M serving multilingual use cases. List Models: List all available models using the command: ollama list. 1 on English academic benchmarks. Other Potential Models: Future integrations could include Jun 15, 2024 路 ollama run <model_name> Model Library and Management. 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. png files using file paths: Browse Ollama's library of models. For vision, Llama 4 models are also optimized for visual recognition, image reasoning, captioning, and answering general questions about an image. 5. DeepSeek-V3 achieves a significant breakthrough in inference speed over previous models. ollama run qwen3:14b 32B parameter model. Sep 21, 2024 路 Vision Models: Multimodal models that accept text and images, useful for image captioning and visual question answering. mistral-small3. List Models from Ollama Library This API fetches available models from the Ollama library page, including details such as the model's name, pull count, popular tags, tag count, and the last update time. The Llama 3. 7B, 13B and a new 34B model: ollama run llava:7b; ollama run llava:13b; ollama run llava:34b; Usage CLI. Pull a Model: Pull a model using the command: ollama pull <model_name> Create a Model: Create a new model using the command: ollama create <model_name> -f <model_file> Remove a Model: Remove a model using the command Nov 8, 2024 路 From OCR, image recognition, and document retrieval to complex multimodal pipelines, OLLAMA’s Vision models provide the tools needed to innovate and build cutting-edge AI applications. 1. 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. 2 collection of multilingual large language models (LLMs) is a collection of pretrained and instruction-tuned generative models in 1B and 3B sizes (text in/text out). . ollama run qwen3:0. jpg or . Search for Vision models on Ollama. OLMo 2 is a new family of 7B and 13B models trained on up to 5T tokens. ytkkufbfrjwcankkqmcrtnyfsktthzmsdpjkiqxshaujwoqeseje