Ollama v0.40.4 釋出決策模型支援、MLX 性能提升與 Codex 模型切換功能

v0.40.4

AI 導讀

Ollama v0.40.4 釋出，CLI 可直接執行決策模型、提升 MLX 執行效能、加入多模態嵌入並在 Codex CLI 中可切換本機模型。

決策模型：可透過 ollama run 直接在終端問答、分類或評分。

推薦理由

v0.40.4 讓 Ollama CLI 可直接執行決策模型、提升 MLX 效能，並加入多模態嵌入與 Codex 模型切換，使用者可即時評估工作流程。

正文 · 原文

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