llm 0.33 Simon Willison released llm 0.33, a command-line tool for running LLMs, which adds a --key option to llm embed and llm embed-multi commands and corresponding Python methods, allowing per-call keys for embedding plugins. The release also enables repeating -t/--template to combine templates, and adds a reasoning_summary option for reasoning-capable Responses API models. The update follows a quick 0.32.1 fix and includes contributions from ChrisJr404. Release: llm 0.33 https://github.com/simonw/llm/releases/tag/0.33 My highlights from this release: I shipped a quick 0.32.1 fix https://simonwillison.net/2026/Aug/21/llm/ for this yesterday, but this is the more comprehensive fix. llm embed and llm embed-multi now accept --key . The Python EmbeddingModel.embed , EmbeddingModel.embed multi , Collection.embed and Collection.embed multi methods accept key= too, passing the resolved per-call key to embedding plugins without changing shared model state. Existing plugins that read self.key continue to work through a compatibility fallback. Thanks, ChrisJr404 . 757 , 1620 The embedding models now use the same pattern for keys that regular LLM models do. llm prompt -t/--template can now be repeated to combine templates in order. This allows model configuration and options from one template to be used with a prompt from another. This unlocks a neat pattern where you can create templates that package a model with a set of default options: llm -m gpt-5.6-luna -o reasoning effort high --save lhigh llm "Generate an SVG of a pelican riding a bicycle" --save pelican Combine and run the templates llm -t lhigh -t pelican - Reasoning-capable Responses API models now support a reasoning summary option with auto , concise , and detailed values. This can be used with llm openai endpoint --responses . 1600 This is particularly useful for exercising different models that provide their own imitation of the OpenAI Responses API. Tags: annotated-release-notes https://simonwillison.net/tags/annotated-release-notes , llm https://simonwillison.net/tags/llm