Cloud models are now in preview, letting you run larger models with fast, datacenter-grade hardware. You can keep using your local tools while running larger models that wouldn’t fit on a personal computer.
Ollama partners with OpenAI to bring gpt-oss to Ollama and its community.
Ollama's new app is now available for macOS and Windows.
Secure Minions is a secure protocol built by Stanford's Hazy Research lab to allow encrypted local-remote communication.
Ollama now has the ability to enable or disable thinking. This gives users the flexibility to choose the model’s thinking behavior for different applications and use cases.
Ollama now supports streaming responses with tool calling. This enables all chat applications to stream content and also call tools in real time.
Ollama now supports new multimodal models with its new engine.
Avanika Narayan, Dan Biderman, and Sabri Eyuboglu from Christopher Ré's Stanford Hazy Research lab, along with Avner May, Scott Linderman, James Zou, have developed a way to shift a substantial portion of LLM workloads to consumer devices by having small on-device models (such as Llama 3.2 with Ollama) collaborate with larger models in the cloud (such as GPT-4o).
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.
With Ollama Python library version 0.4, functions can now be provided as tools. The library now also has full typing support and new examples have been added.
Llama 3.2 Vision 11B and 90B models are now available in Ollama.
Ollama partners with IBM to bring Granite 3.0 models to Ollama.
Ollama partners with Meta to bring Llama 3.2 to Ollama.
Bespoke-Minicheck is a new grounded factuality checking model developed by Bespoke Labs that is now available in Ollama. It can fact-check responses generated by other models to detect and reduce hallucinations.
Ollama now supports tool calling with popular models such as Llama 3.1. This enables a model to answer a given prompt using tool(s) it knows about, making it possible for models to perform more complex tasks or interact with the outside world.
Gemma 2 is now available on Ollama in 3 sizes - 2B, 9B and 27B.
Continue enables you to easily create your own coding assistant directly inside Visual Studio Code and JetBrains with open-source LLMs.
At Google IO 2024, Google announced Ollama support in Firebase Genkit, a new open-source framework for developers to build, deploy and monitor production-ready AI-powered apps.
Compared to Llama 2, Llama 3 feels much less censored. Meta has substantially lowered false refusal rates. Llama 3 will refuse less than 1/3 of the prompts previously refused by Llama 2.
Llama 3 is now available to run on Ollama. This model is the next generation of Meta's state-of-the-art large language model, and is the most capable openly available LLM to date.
Embedding models are available in Ollama, making it easy to generate vector embeddings for use in search and retrieval augmented generation (RAG) applications.
Ollama now supports AMD graphics cards in preview on Windows and Linux. All the features of Ollama can now be accelerated by AMD graphics cards on Ollama for Linux and Windows.
Ollama is now available on Windows in preview, making it possible to pull, run and create large language models in a new native Windows experience. Ollama on Windows includes built-in GPU acceleration, access to the full model library, and serves the Ollama API including OpenAI compatibility.
Ollama now has initial compatibility with the OpenAI Chat Completions API, making it possible to use existing tooling built for OpenAI with local models via Ollama.
New vision models are now available: LLaVA 1.6, in 7B, 13B and 34B parameter sizes. These models support higher resolution images, improved text recognition and logical reasoning.
The initial versions of the Ollama Python and JavaScript libraries are now available, making it easy to integrate your Python or JavaScript, or Typescript app with Ollama in a few lines of code. Both libraries include all the features of the Ollama REST API, are familiar in design, and compatible with new and previous versions of Ollama.
Recreate one of the most popular LangChain use-cases with open source, locally running software - a chain that performs Retrieval-Augmented Generation, or RAG for short, and allows you to “chat with your documents”
Ollama can now run with Docker Desktop on the Mac, and run inside Docker containers with GPU acceleration on Linux.
This post walks through how you could incorporate a local LLM using Ollama in Obsidian, or potentially any note taking tool.
This guide walks through the different ways to structure prompts for Code Llama and its different variations and features including instructions, code completion and fill-in-the-middle (FIM).
Meta's Code Llama is now available on Ollama to try.
This post will give some example comparisons running Llama 2 uncensored model versus its censored model.