# llm 0.33

> Source: <https://simonwillison.net/2026/Aug/22/llm/>
> Published: 2026-08-22 17:01:16+00:00

**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)