Ollama v0.40.4 支援在終端直接執行決策模型

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