Download Ollama

Pin this version: winget install --id Ollama.Ollama --version 0.40.14 --exact

What's Changed - ollama launch claude now applies the model's output token limit for Claude Code, so cloud models no longer run into the 128k default cap - Cloud web search responses on /api/chat are now decoded correctly, including compressed responses - OpenAI-compatible endpoints no longer override a model's packaged sampler defaults — clients that send no temperature/top_p get the model's own values instead of 1.0, matching /api/chat - /v1/responses now preserves readable input content, including prior assistant refusals, instead of flattening it - Ollama's app can now retry ChatGPT disconnect failures instead of leaving the connection in a broken state - ollama launch codex verifies ChatGPT routing before configuring, and reports a clear error when routing is unavailable - Faster top-k sampling on MLX for large vocabularies Full Changelog: https://github.com/ollama/ollama/compare/v0.40.13...v0.40.14

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Manifest: manifests/o/Ollama/Ollama/0.40.14

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LFM3 on Linux and Windows Liquid AI's LFM3 models, including text-to-speech in lfm3-audio and lfm3-omni, now run on Linux and Windows as well as Apple silicon. Full Changelog: https://github.com/ollama/ollama/compare/v0.40.12...v0.40.13

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Manifest: manifests/o/Ollama/Ollama/0.40.13

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Liquid AI LFM3 LFM3 is Liquid AI's new family of small models built for local agents, tool calling, and structured output, on Liquid's new tri-hybrid architecture. The family includes: - lfm3: a 1.7B text model with a 256K-token context window - lfm3-vl: adds image understanding - lfm3-audio: speech recognition, translation, and text-to-speech in 18 languages - lfm3-omni: text, images, and audio in one model ollama run lfm3 d1 decision models Liquid AI's d1 models now come in a 2B size, built on LFM3. d1 makes decisions about text and images, and d1-omni adds audio. ollama run d1:2b "I was charged twice for order 4417." --ask "Is this a billing issue?" Note: lfm3 and d1 2b are supported on Apple hardware in this release. Support for Linux/Windows coming soon. What's Changed - Faster prompt processing on Apple silicon for Gemma 4, Flint and Laguna models - Speculative decoding now supports DFlash2 draft models on MLX - Gemma 4 keeps more detail in small images - ollama launch now works with OpenCode v2 - Fixed tool-only assistant turns from Kimi CLI - Updated MLX and llama.cpp Full Changelog: https://github.com/ollama/ollama/compare/v0.40.11...v0.40.12

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Manifest: manifests/o/Ollama/Ollama/0.40.12

Pin this version: winget install --id Ollama.Ollama --version 0.40.11 --exact

Speech Ollama can now generate speech on macOS. ollama run plays text or a chat model's reply aloud as the audio is generated, and apps can stream audio through the OpenAI-compatible /v1/audio/speech endpoint. ollama run phonon "Hello from Ollama." d3 decision models d3 brings vLLM Semantic Router's decision models to Ollama. Give a model text, structured state, or an image, and ask it to classify, answer yes or no, or score options with probabilities. The family includes 2B, 4B, 9B, and 27B sizes. ollama run d3 "A customer says their card was charged twice." --ask "Is this a billing issue?" New Contributors - @SynapShift made their first contribution in https://github.com/ollama/ollama/pull/19173 Full Changelog: https://github.com/ollama/ollama/compare/v0.40.10...v0.40.11-rc0

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Manifest: manifests/o/Ollama/Ollama/0.40.11

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NVIDIA Nemotron 3.5 Bolt E4B Nemotron 3.5 Bolt E4B is NVIDIA’s smaller, Gemma 4-based vision-language model for fast local conversations, image understanding, and tool use. It supports a 128K-token context window. The model includes a DFlash draft for speculative decoding. ollama run nemotron-3.5-bolt:e4b Full Changelog: https://github.com/ollama/ollama/compare/v0.40.9...v0.40.10

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Manifest: manifests/o/Ollama/Ollama/0.40.10

Pin this version: winget install --id Ollama.Ollama --version 0.40.9 --exact

Speech Ollama can now generate speech with Phonon on Apple Silicon. ollama run plays text or a chat model's reply aloud as the audio is generated, and apps can stream audio through the OpenAI-compatible /v1/audio/speech endpoint. ollama run phonon "Hello from Ollama." d3 decision models d3 brings vLLM Semantic Router's decision models to Ollama. Give a model text, structured state, or an image, and ask it to classify, answer yes or no, or score options with probabilities. The family includes 2B, 4B, 9B, and 27B sizes. ollama run d3 "A customer says their card was charged twice." --ask "Is this a billing issue?" Flint on Linux and Windows Flint now runs on Linux and Windows as well as macOS. Other improvements - Streaming OpenAI Responses and Anthropic Messages requests now report generation failures instead of ending silently after partial output. - ollama launch now passes cloud models' context lengths and capabilities to coding tools, fixing incorrect context and compaction settings. - Anthropic-compatible web search now uses the model's supported thinking setting in follow-up requests, preventing avoidable failures. Full Changelog: https://github.com/ollama/ollama/compare/v0.40.8...v0.40.9

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Manifest: manifests/o/Ollama/Ollama/0.40.9

Pin this version: winget install --id Ollama.Ollama --version 0.40.8 --exact

Recursive Flint Flint brings Recursive's coding model to Ollama. It is designed for the work coding agents do across a repository: understanding unfamiliar code, tracing bugs, implementing features, and adding tests. Reasoning, multi-turn tool use, and a 262K-token context window support longer tasks across files and tool interactions. Flint is an Apache 2.0-licensed, 40B-parameter mixture-of-experts model with approximately 2.5B parameters active per token. In its release evaluations, Recursive reports 54.9% on Terminal-Bench 2.1 and 74.2% on SWE-bench Verified. ollama run flint Note: Flint is supported on MacOS. Other GPU support will be enabled in a subsequent release. Full Changelog: https://github.com/ollama/ollama/compare/v0.40.7...v0.40.8

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Manifest: manifests/o/Ollama/Ollama/0.40.8

Pin this version: winget install --id Ollama.Ollama --version 0.40.7 --exact

What's Changed - pplx-decider is a 27B decision model from Perplexity, fine-tuned from Qwen3.8-27B - Continuing an OpenAI-compatible Responses conversation no longer fails when switching between models with and without thinking, or when the history contains another provider's compaction items - Fixed streaming Responses requests where client tool calls (e.g. Codex with web search) could emit before open reasoning items, producing misordered/duplicate tool call events - Requests routed to remote models are now cancelled on ollama.com when the client disconnects, instead of continuing to run - ollama show now reports which renderer and parser a model uses and where its chat template comes from; the API exposes the same values in new renderer, parser, and template_source fields - More draft models now work with speculative decoding: llama-server infers the draft type automatically instead of requiring Ollama to identify it - ollama launch claude now clamps CLAUDE_CODE_AUTO_COMPACT_WINDOW to Claude Code's supported range, avoiding a "window too large" warning - Updated llama.cpp and MLX Full Changelog: https://github.com/ollama/ollama/compare/v0.40.6...v0.40.7

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Manifest: manifests/o/Ollama/Ollama/0.40.7

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What's Changed - win: prevent orphaned runners by @dhiltgen in https://github.com/ollama/ollama/pull/18500 - gguf: add the q2_0 tensor and file types by @jmorganca in https://github.com/ollama/ollama/pull/18967 - Launch clef in Ollama's cloud by @jberg5 in https://github.com/ollama/ollama/pull/19036 - use identifiers for --ask mode question keys by @jberg5 in https://github.com/ollama/ollama/pull/19041 Full Changelog: https://github.com/ollama/ollama/compare/v0.40.5...v0.40.6-rc0

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Manifest: manifests/o/Ollama/Ollama/0.40.6

Pin this version: winget install --id Ollama.Ollama --version 0.40.5 --exact

NVIDIA Nemotron 3.5 Super NVIDIA Nemotron 3.5 Super is a vision-language model for coding, reasoning, tool use, and document understanding. It pairs a 120B-parameter hybrid Mamba-2/Transformer mixture-of-experts backbone (12B active per token) with a C-RADIO vision encoder, and supports tool calling, an on/off thinking mode, and context up to 1M tokens. ollama run nemotron-3.5-super A compact sibling, Nemotron 3.5 Bolt, distills Super down to 74B parameters (9B active) tuned to fit a 24 GB NVIDIA GPU for everyday agentic tasks, with speculative decoding via its included drafter. What's Changed - Decision models are now available on cloud — use clef:cloud and clef-flash:cloud to run decision models through ollama.com cloud without pulling them locally - Continuing an OpenAI-compatible Responses conversation that includes custom tool calls no longer fails with an error - Clearer error messages when cloud access fails: sign-in problems, payment issues in the desktop app, and upstream access errors from the ChatGPT gateway now explain what went wrong - Updated llama.cpp (adding Nemotron 3.5 support) and MLX New Contributors - @willietran made their first contribution in https://github.com/ollama/ollama/pull/18986 Full Changelog: https://github.com/ollama/ollama/compare/v0.40.4...v0.40.5

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Manifest: manifests/o/Ollama/Ollama/0.40.5

Pin this version: winget install --id Ollama.Ollama --version 0.40.4 --exact

Decision models in the CLI Decision models can now be used directly from the terminal with ollama run — ask yes/no questions, classify text into labels, or score against a rubric: ollama run nimble --ask "Is a refund being requested?" < ticket.txt What's Changed - Kev decision models are now supported by the MLX runner on Apple silicon - ollama launch can now be used with usage credits without upgrading to a paid plan - ollama launch codex now includes locally installed Ollama models in its model picker. Use /model within the Codex CLI to swap models. - Improved inference performance by reusing verified manifests and already loaded models - Added support for multimodal embeddings through llama-server - Fixed loading multimodal embedding models with small context windows - Improved Gemma 4 prefill performance on NVIDIA GPUs with the MLX runner - MLX runner now clips long Laya states instead of rejecting them - Improved speculative decoding reliability in the MLX runner, including recurrent state handling after rollback - Updated llama.cpp with native decision model support - Updated README and documentation with clearer privacy and cloud-services wording Full Changelog: https://github.com/ollama/ollama/compare/v0.40.3...v0.40.4

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Manifest: manifests/o/Ollama/Ollama/0.40.4

Pin this version: winget install --id Ollama.Ollama --version 0.40.3 --exact

What's Changed - ollama launch claude no longer shows a warning about Claude connectors by @hoyyeva in https://github.com/ollama/ollama/pull/18878 - ollama launch codex no longer warns about service tiers by @hoyyeva in https://github.com/ollama/ollama/pull/18879 - Paused background model upgrade for embedding and other request performance, by @jmorganca in https://github.com/ollama/ollama/pull/18908 Full Changelog: https://github.com/ollama/ollama/compare/v0.40.2...v0.40.3

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Manifest: manifests/o/Ollama/Ollama/0.40.3

Pin this version: winget install --id Ollama.Ollama --version 0.40.2 --exact

Model upgrades Models downloaded with earlier versions of Ollama are upgraded in the background the first time you run them, for better performance and compatibility when running on llama.cpp. To make downgrading safe, Ollama keeps the original copy as a backup, so upgraded models are temporarily kept on disk. A future release will remove these backups automatically. To remove backed up models now (requires jq): curl -s localhost:11434/api/tags | jq -r '.models[].name' | while read -r m; do curl -s localhost:11434/api/show -d "{\"model\":\"$m\"}" | jq -r \ 'select(any(.manifests[]?; .runner == "llamacpp")) | .manifests[] | select(.runner == "ggml") | .digest' done | sort -u | xargs -n1 ollama rm This only deletes the backups. If you later downgrade to a version older than 0.40, you'll need to re-pull those models. Other changes - ollama list no longer shows duplicate entries for upgraded models by @dhiltgen in https://github.com/ollama/ollama/pull/18874 - ollama launch claude uses the model's full context length by @jberg5 in https://github.com/ollama/ollama/pull/18855 - README: add oxi to community integrations by @maziluiosif in https://github.com/ollama/ollama/pull/18739 New Contributors - @maziluiosif made their first contribution in https://github.com/ollama/ollama/pull/18739 Full Changelog: https://github.com/ollama/ollama/compare/v0.40.1...v0.40.2-rc0

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Manifest: manifests/o/Ollama/Ollama/0.40.2

Pin this version: winget install --id Ollama.Ollama --version 0.40.1 --exact

What's Changed - server: proxy cloud usage and balance APIs by @drifkin in https://github.com/ollama/ollama/pull/18829 - llama: fix clef head reads past 2GiB on windows by @Gigrise in https://github.com/ollama/ollama/pull/18777 - cmd: remove account step from CLI onboarding by @hoyyeva in https://github.com/ollama/ollama/pull/18826 - manifest: avoid symlinks on Windows by @dhiltgen in https://github.com/ollama/ollama/pull/18852 - docs: fix 6 dead links in README community integrations list by @aniketkrs in https://github.com/ollama/ollama/pull/18814 - docs: fix broken download links in app README by @chenlichao in https://github.com/ollama/ollama/pull/18233 - mlx: drop carried metal residency patch now that it is upstream by @dhiltgen in https://github.com/ollama/ollama/pull/18854 New Contributors - @Gigrise made their first contribution in https://github.com/ollama/ollama/pull/18777 - @aniketkrs made their first contribution in https://github.com/ollama/ollama/pull/18814 - @chenlichao made their first contribution in https://github.com/ollama/ollama/pull/18233 Full Changelog: https://github.com/ollama/ollama/compare/v0.40.0...v0.40.1-rc0

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Manifest: manifests/o/Ollama/Ollama/0.40.1

Pin this version: winget install --id Ollama.Ollama --version 0.40.0 --exact

What's Changed Models run on MLX on Apple Silicon by default In this release, on Apple Silicon devices, model architectures supported by the MLX runtime will automatically run on MLX. ollama pull qwen3.8 ollama run qwen3.8 Additional models include gemma4, qwen3.6 and qwen3.5 Decision models are now available on MLX as well: Nimble tev1 clef clef-flash MLX now has support for an embedding model: embeddinggemma-2 We will continue testing and enabling additional models. Full Changelog: https://github.com/ollama/ollama/compare/v0.35.1...v0.40.0

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Manifest: manifests/o/Ollama/Ollama/0.40.0

Pin this version: winget install --id Ollama.Ollama --version 0.35.1 --exact

Clef decision models Ollama now supports Clef and Clef Flash, Cloudflare's new open-source decision models, through /v1/systemone. Clef (27B) and Clef Flash (9B) are multimodal: requests can now include images alongside the text state, shared by all questions and scored jointly with it. curl http://localhost:11434/v1/systemone -d '{ "model": "clef-flash", "state": "The user took this screenshot.", "images": ["<base64-encoded image>"], "questions": { "has_ollama": {"type": "noul", "instructions": "Does this image contain Ollama?"} } }' { "model": "clef-flash", "answers": { "has_ollama": { "type": "noul", "noul": 0.958 } }, "usage": { "input_tokens": 548, "output_tokens": 0 } } What's Changed - Models using web search can now perform up to ten searches per response, up from three - Modelfiles now support CAPABILITY declarations, so model creators can explicitly declare what a model can do. Declarations are preserved when creating from GGUF or safetensors, through model inheritance, and on Modelfile export - ollama show and the model list now report only decision as the capability for decision models, so clients no longer offer them for general chat, tools, or thinking - Updated llama.cpp and the MLX engine Full Changelog: https://github.com/ollama/ollama/compare/v0.35.0...v0.35.1

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Manifest: manifests/o/Ollama/Ollama/0.35.1

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Decision models Ollama now supports decision models through /v1/systemone, based on TypeSafe’s Jev API. Decision models return choices, probabilities, and scores instead of text. Use them for tasks such as ticket triage, model routing, and content classification. Available models: - Nimble from Bespoke Labs - Tev1 from Together AI ollama pull nimble Send context and one or more questions: curl http://localhost:11434/v1/systemone \ -H 'Content-Type: application/json' \ -d '{ "model": "nimble", "state": "Our checkout has returned 500 errors since 9am.", "questions": { "label": { "type": "choice", "instructions": "Which label fits this ticket?", "criteria": { "billing": "Payments and refunds", "bug": "Software errors", "account": "Login and account access" } } } }' Example response: { "model": "nimble", "answers": { "label": { "type": "choice", "choice": "bug", "probabilities": { "billing": 0.0125, "bug": 0.9781, "account": 0.0093 }, "confidence": 0.8906 } }, "usage": { "input_tokens": 174, "output_tokens": 1 } } The API supports three question types: - choice: Select an option and return probabilities for each. - noul: Return the probability that a condition is true. - score: Return a score across an ordered set of criteria What's Changed - Settings now opens without waiting for model discovery. - Fixed the macOS update menu and icon not reflecting an available update at startup. - Fixed stalled MLX model downloads hanging indefinitely. - Requests containing the deprecated…

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Manifest: manifests/o/Ollama/Ollama/0.35.0

Pin this version: winget install --id Ollama.Ollama --version 0.34.4 --exact

What's Changed - Structured outputs on thinking models now apply in a single pass, making them faster and more reliable. - Fixed intermittent "model not found" errors with a large local library - Fixed the macOS app becoming unresponsive when checking if ChatGPT or Codex is running. - Qwen 3.8 prompt processing is faster on Apple Silicon. - Gemma 4 on Apple Silicon now picks the best image resolution per image, keeping more detail in high-resolution images. - Updated llama.cpp, MLX, and XGrammar. Full Changelog: https://github.com/ollama/ollama/compare/v0.34.3...v0.34.4

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Manifest: manifests/o/Ollama/Ollama/0.34.4

Pin this version: winget install --id Ollama.Ollama --version 0.34.3 --exact

What's Changed GET /api/show now advertises each model's thinking controls and default: Available in the CLI with: ollama show gemma4 thinking levels false, true default true Available in the API with: curl http://localhost:11434/api/show -d '{"model": "glm-5.3-flash:cloud"}' { "thinking": { "values": ["low", "high", "max"], "default": "max" } } Also available on ollama.com directly for cloud models. - Nemotron H vision models are now supported on Apple Silicon with MLX - Ollama's macOS app will now no longer reopen windows you've closed when activating it - Fix for model pulls from HuggingFace Full Changelog: https://github.com/ollama/ollama/compare/v0.34.2...v0.34.3

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Manifest: manifests/o/Ollama/Ollama/0.34.3

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What's Changed - Added first-run setup when running ollama, with options to sign in or continue locally. Setup completion is shared with the desktop app on macOS and Windows. - Added ollama://apps to open the desktop app’s Apps page directly on macOS and Windows. - Fixed excessive memory growth during long generations with MLX speculative decoding. - Updated llama.cpp. Full Changelog: https://github.com/ollama/ollama/compare/v0.34.1...v0.34.2

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Manifest: manifests/o/Ollama/Ollama/0.34.2