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Ollama

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  • Speech models in Ollama
    Ollama now supports speech models, starting with Phonon from Gradium. Read text aloud in five languages and dozens of voices, streamed as it is generated, over 100 times faster than real time on Apple Silicon.
  • Clef is available on Ollama's cloud
    Clef, a 27B multimodal decision model from Cloudflare, is now available on Ollama. Run it locally or on Ollama's cloud.
  • Reflection's Beam is freely available on Ollama for a limited time
    Reflection's first open-weight model is now available on Ollama, and free for a limited time only. Beam is designed for software engineering, reasoning, and long-running agentic tasks. Access Beam through Ollama's cloud.
  • Run AI agents safely with Ollama and Fly.io
    AI agents can now use Ollama's cloud models safely inside Fly.io's cloud computers.
  • Ollama now supports Jev-style decision models
    Ollama now supports decision models, based on TypeSafe's Jev API for fast, typed decisions. Decision models can now be run at no cost with low latency. Based on text, decision models answer yes-or-no questions, choices and scores about it, with a probability for every option.
  • Ollama's transparent pricing
    Ollama's Pro, Max, and Team plans now use industry-standard per-token pricing with usage included on every plan.
  • Claude Desktop support with Ollama
    Claude Desktop can now be configured to work with Ollama as a third-party gateway provider, making it possible to use open models in Claude.
  • NVIDIA Nemotron 3.5 Lightning
    NVIDIA Nemotron 3.5 Lightning is now available on Ollama. It's a 30 billion parameter (3B active) open model built for agents that stay running, gathering context, calling tools, and working through multi-step tasks on your own hardware.
  • Muse Glimmer from Meta Superintelligence Labs is now available
    Meta's Muse Glimmer, the first open model released by Meta Superintelligence Labs, is now available. Muse Glimmer is a 30B multimodal model released under the Apache 2.0 license, designed for local coding agents, and accelerated by Ollama's MLX engine with new native DFlash and image input support.
  • Ollama: all aboard open models
    Serving 8.9 million developers, Ollama has raised $88M from Benchmark, Theory Ventures, 8VC, Y Combinator, and many incredible angel investors.

ℹ️ Plus d’infos via Wikipédia

Ollama

Ollama
DevelopersOllama Inc. and contributors
ReleaseJuly 8, 2023; 3 years ago (2023-07-08)
Stable release
0.40.10[1] Edit this on Wikidata / 23 October 2026; 2 days ago (23 October 2026)
Written inGo, C, TypeScript
Operating systemmacOS, Linux, Windows
TypeLarge language model runtime
LicenseMIT License
Websiteollama.com Edit this on Wikidata
Repository

Ollama is an open-source software platform developed by Jeffrey Morgan and Michael Chiang in 2023 for running and managing large language models on local GPU infrastructure and through hosted cloud models. It provides a command-line interface, a native GUI, a local REST API, model-management tools, and integrations for using open-weight models with coding assistants and other applications.[2][3][4]

History

Ollama was first released in July 8, 2023.[5] The project became associated with the growth of local large language model software, allowing users to download and run models such as Llama, Gemma, Mistral, Qwen, gpt-oss, GLM and DeepSeek on a local machine.[2]

In 2025 and 2026, Ollama added additional application and cloud features, including hosted cloud models, web search support, tool and coding-agent integrations, and support for using Ollama with applications such as Claude Code, Codex, OpenCode, Copilot CLI,[6] and OpenClaw.[3][7] In March 2026, Ollama announced preview support for Apple silicon.[8]

In July 2026, the company has raised $65 million dollars in funding.[9]

Features

Ollama running Llama 3 in Linux

Ollama includes tools for downloading, running, importing, and managing large language models. Users can run models from the command line, interact with them through a local HTTP API, or use client libraries for programming languages such as Python and JavaScript.[2]

The project provides a REST API for chat and model-management functions, with the default local service commonly exposed on port 11434.[10] Ollama also distributes an official Docker image and provides model libraries and documentation for running supported models.[2]

Ollama uses the llama.cpp backend for local model inference.[11] It supports a model-library format that allows users to pull, run, and manage model variants by name.[12]

Meanwhile, the project's downloadable software is being explored as a back-end platform for low-code/no-code self-hosting of LLMs, potentially allowing natural language processing use cases to become more accessible to nontechnical end users.[13][14]

Ollama also has experimental support for image generation, using models such as Flux, on macOS, with Windows and Linux support expected in the future.[15]

Security

Because Ollama is commonly used to run local or self-hosted AI models, security researchers have examined risks from misconfigured public deployments. In January 2026, research by SentinelOne and Censys found many Ollama servers were exposed to the public internet, mainly by binding to the INADDR_ANY interface (0.0.0.0) which on an inadequately-secured system would allow access from other local or remote devices despite the fact that Ollama is intended to run locally by default.[16]

See also

References

  1. ↑ "Release 0.40.10". October 23, 2026. Retrieved October 24, 2026.
  2. 1 2 3 4 "ollama/ollama". GitHub. Retrieved April 29, 2026.
  3. 1 2 "Ollama". Ollama. Retrieved April 29, 2026.
  4. ↑ SitePoint Team (April 22, 2026). "10GB VRAM Local LLM: The Complete Setup Guide (2026)". SitePoint. Retrieved April 29, 2026.
  5. ↑ "Release v0.0.1". github.com. Retrieved August 31, 2026.
  6. ↑ "About GitHub Copilot CLI". GitHub Docs. GitHub. Retrieved April 29, 2026.
  7. ↑ "Blog". Ollama. Retrieved April 29, 2026.
  8. ↑ Medina, David (March 31, 2026). "Ollama Taps Apple's MLX Framework to Make Local AI Faster". The New Stack. Retrieved April 29, 2026.
  9. ↑ Bort, Julie (July 9, 2026). "Popular open source AI developer tool Ollama raises $65M, grows to nearly 9M users". TechCrunch. Retrieved July 12, 2026.
  10. ↑ "API reference". Ollama Docs. Retrieved April 29, 2026.
  11. ↑ "Forensic Implications of Localized AI: Artifact Analysis of Ollama, LM Studio, and llama.cpp". arxiv.org. Retrieved May 22, 2026.
  12. ↑ "Library". Ollama. Retrieved April 29, 2026.
  13. ↑ Sempio, Julius (March 31, 2026). "Low-Code Self-Hosting of RAG-Enabled Language Models Using Ollama and Open WebUI". IEEE Xplore. doi:10.1109/ICAIIC68212.2026.11454259. Retrieved May 20, 2026.
  14. ↑ "Low-Code vs. No-Code: What's the difference?". IBM Cloud Education. Retrieved June 4, 2026.
  15. ↑ Kemper, Jonathan (January 21, 2026). "Ollama brings local AI image generation to Mac". The Decoder. Retrieved May 22, 2026.
  16. ↑ Fadilpašić, Sead (September 2, 2025). "Hundreds of LLM servers left exposed online - here's what we know". TechRadar. Retrieved October 12, 2026.
Source Wikipédia (CC BY-SA 4.0) : https://en.wikipedia.org/wiki/Ollama
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