GitHub Release: ollama/ollama v0.40.4 (14.10.2026)

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: v0.40.3...v0.40.4