Data and AI releases

548 this month · 176 companies

Ollama, September 2026 new features

7 releases · 1 product

Ollama 0.35.1

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.

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Ollama 0.35.0

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.

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Ollama 0.40.0

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.

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Ollama 0.34.4

- 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.

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Ollama 0.34.3

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...

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Ollama 0.34.2

- 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.

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Ollama 0.34.1

- MLX safetensors ollama create no longer experimental. GGUF model creation now requires using llama.cpp tooling for safetensor conversion and quantization. - Improved MLX memory handling on Apple Silicon - Runaway repeat token detection now requires 100 repeat tokens for reduced false positives (e.g.

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