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Welcome OpenAI’s gpt-oss! Ollama partners with OpenAI to bring its latest state-of-the-art open weight models to Ollama. The two models, 20B and 120B, bring a whole new local chat experience, and are designed for powerful reasoning, agentic tasks, and versatile developer use cases. Get started You can get started by downloading the latest Ollama version. The model can be downloaded directly in Oll

Ollama's new app July 30, 2025 Ollama’s new app is now available for macOS and Windows. An easier way to chat with models Ollama’s macOS and Windows now include a way to download and chat with models. Chat with files Ollama’s new app supports file drag and drop, making it easier to reason with text or PDFs. For processing large documents, Ollama’s context length can be increased in the settings. N

Usage and Limitations These models have certain limitations that users should be aware of. Intended Usage Open generative models have a wide range of applications across various industries and domains. The following list of potential uses is not comprehensive. The purpose of this list is to provide contextual information about the possible use-cases that the model creators considered as part of mo

 > This model requires Ollama 0.6 or later. [Download Ollama](https://ollama.com/download) Gemma is a lightweight, family of models from Google built on Gemini technology. The Gemma 3 models are multimodal—processing text and images—and feature a 128K context window with support for over 140 languages. Available in

DeepSeek’s first-generation reasoning models, achieving performance comparable to OpenAI-o1 across math, code, and reasoning tasks. Models DeepSeek-R1 ollama run deepseek-r1:671b Distilled models DeepSeek team has demonstrated that the reasoning patterns of larger models can be distilled into smaller models, resulting in better performance compared to the reasoning patterns discovered through RL o

Phi-4 is a 14B parameter, state-of-the-art open model built upon a blend of synthetic datasets, data from filtered public domain websites, and acquired academic books and Q&A datasets. The model underwent a rigorous enhancement and alignment process, incorporating both supervised fine-tuning and direct preference optimization to ensure precise instruction adherence and robust safety measures. Cont

Structured outputs December 6, 2024 Ollama now supports structured outputs making it possible to constrain a model’s output to a specific format defined by a JSON schema. The Ollama Python and JavaScript libraries have been updated to support structured outputs. Use cases for structured outputs include: Parsing data from documents Extracting data from images Structuring all language model response

Ollama Python library 0.4 with function calling improvements November 25, 2024 In the latest version of the Ollama Python library, functions can now be provided as tools. The library now also has full typing support and new examples have been added. Get started Start by installing or upgrading the Ollama Python library: pip install -U ollama Passing Python functions as tools Define a Python functi

Llama 3.2 Vision November 6, 2024 Llama 3.2 Vision is now available to run in Ollama, in both 11B and 90B sizes. Get started Download Ollama 0.4, then run: ollama run llama3.2-vision To run the larger 90B model: ollama run llama3.2-vision:90b To add an image to the prompt, drag and drop it into the terminal, or add a path to the image to the prompt on Linux. Note: Llama 3.2 Vision 11B requires lea

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Usage To generate vector embeddings, first pull a model: ollama pull mxbai-embed-large Next, use the REST API, Python or JavaScript libraries to generate vector embeddings from the model: REST API curl http://localhost:11434/api/embed -d '{ "model": "mxbai-embed-large", "input": "Llamas are members of the camelid family" }' Python library ollama.embed( model='mxbai-embed-large', input='Llamas are

OpenAI compatibility February 8, 2024 Ollama now has built-in compatibility with the OpenAI Chat Completions API, making it possible to use more tooling and applications with Ollama locally. Setup Start by downloading Ollama and pulling a model such as Llama 2 or Mistral: ollama pull llama2 Usage cURL To invoke Ollama’s OpenAI compatible API endpoint, use the same OpenAI format and change the host

Python & JavaScript Libraries January 23, 2024 The initial versions of the Ollama Python and JavaScript libraries are now available: Ollama Python Library Ollama JavaScript Library Both libraries make it possible to integrate new and existing apps with Ollama in a few lines of code, and share the features and feel of the Ollama REST API. Getting Started Python pip install ollama import ollama resp

Building LLM-Powered Web Apps with Client-Side Technology October 13, 2023 This is a guest blog post by Jacob Lee, JS/TS maintainer at @LangChainAI, formerly co-founder & CTO at @Autocode, engineer on Google photos. The initial version of this blog post was a talk for Google’s internal WebML Summit 2023, which you can check out here: It’s no secret that for a long time machine learning has been mo

OpenAI’s open-weight models designed for powerful reasoning, agentic tasks, and versatile developer use cases.

Run Llama 2 uncensored locally August 1, 2023 In May 2023, Eric Hartford, a machine learning engineer authored a popular blog post “Uncensored Models” providing his viewpoints to the merits of uncensored models, and how they are created. It’s a great read! This post will give some example comparisons running Llama 2 uncensored model vs its censored model. Some of the uncensored models that are ava

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