Simon Willison’s Weblog

I'm continuing to have a lot of fun with GPT-6 Astra and Blender (see my TIL).

As a big fan of the Imperial Fabergé Easter eggs, I've always thought it would be fun to make some new ones that celebrate popular culture.

Yesterday I decided to try out the new ChatGPT Images 2.5 by running this prompt:

Generate a photo of a faberge egg that's themed after the TV show Pluribus - research first

It gave me this - honestly not bad for a first attempt!

Then, just to see what would happen, I pasted that image into Codex running GPT-6 Astra (high) and prompted:

Use your blender local skill to create a blender model of this faverge egg

(Here's the skill file, which I created like this.)

It churned away for 17m51s and built me several .blend files. I already had this vibe-coded Blender viewing experiment lying around, so I added that to my tools collection and now you can use it to see my Pluribus blender model in your browser:

• New OpenAI model: gpt-6-astra for GPT-6 Astra.

I recorded a short demo video of my Equal Earth animation on my phone and wanted to publish an optimized version of that video (using FFMPEG) on my blog, so I had Claude Fable 5.1 in Claude Code for web build me this tool using the WebAssembly build of FFMPEG.

I got curious about the Equal Earth map projection that was recently voted on at the UN so I had GPT-6 Astra (medium) in ChatGPT Work build me this animated transition between Mercator and Equal Earth using D3.

• Performance fix for loading OpenRouter models. Thanks, waveplate. #59

One new feature:

• llm logs --usage Markdown output now includes the response duration in milliseconds and as a human-readable duration. llm logs --short includes a new duration_ms field. #1653

Plus several contributed bug fixes, and a significant performance improvement to llm logs thanks to waveplate on GitHub, see also llm-openrouter 0.7.1.

Claude Fable 5.1, reasoning traces are now displayed by default for models that support them, plus a new llm_anthropic.ClaudeRefusal exception for when Claude throws a refusal.

• New model gemini-3.8-flash for Gemini 3.8 Flash, with low, medium and high thinking levels. #146
• Fixed async responses failing to record the resolved model version. Thanks, Charlie Tonneslan. #137

Google released Gemini 3.8 Flash (and 3.8 Flash Cyber, but that's available to "trusted defenders" only) today.

Here are the pelicans for high, medium, and low. This is high:

For comparison, here are the same pelicans generated using Gemini 3.7 Flash.

Something I appreciate about Gemini Flash is that it's fast, cheap, and competent at things like HTML and JavaScript. I was messing around with it and prompted "make me a cool thing in html" and it built this, which is certainly a cool thing in HTML! Took 13 seconds, cost 1.8 cents.

If you click through to the demo you'll see one more thing I built with Gemini 3.8 Flash.

My markdown-svg-renderer tool lets me feed in the URL to a Gist with Markdown in and renders that markdown with fenced code blocks for SVG correctly rendered.

I used Gemini 3.8 Flash (with my very basic llm-coding-agent coding agent plugin) to add support for HTML as well, so now any HTML blocks in the Markdown are rendered using a sandboxed iframe. Here's the transcript.

I was helping Natalie gather some maps of local political boundaries (for the Granada Community Services District and the Midcoast Community Council) and found a need to display some GeoJSON files on a map and export that as a PNG. I asked GPT-5.6-Sol for suggestions of tools and it proactively built one. After some iterations using Claude Code for web and Fable 5.1 we got to this finished tool.

As for the GeoJSON.. it turns out if you ask ChatGPT Work to provide boundaries for almost anything it will churn away extracting and combining files from different Government data sources and build exactly what you need.

I got this polygon from:

I want a polygon that represents the exact boundary of the El Granada GCSD

And this one from:

Get me a GeoJSON file for the boundary (or boundaries if that makes sense) for the MCC - Midcoast Community Council - that operates near Half Moon Bay CA

Here's a link that displays both of them at the same time on the new GeoJSON map viewing tool.

• "rows" from execute_sql is now an array of objects. Previously it was an array of arrays. This should help weaker models avoid losing track of which positional array element maps to which column. #1
• Now depends on mcp>=2.1.1.

This is the first non-alpha release of the plugin. I'm confident it's ready as I've been using it quite a bit myself.

This release of the Anthropic plugin for LLM mainly provides compatibility with the recently released anthropic v1.0.0 Python library, which switches from httpx to httpx2. OpenAI made the same change in their v3.0.0 release two weeks ago.

Anthropic provide this migration guide for upgrading to 1.0, so I prompted Fable 5 in Claude Code with:

Upgrade to anthropic>=1 - read https://raw.githubusercontent.com/anthropics/anthropic-sdk-python/refs/heads/main/MIGRATION.md and get the tests passing

Here's the resulting PR.

My highlights from this release:

• Upgraded to the OpenAI Python library 3.x and switched the HTTP client dependency from httpx to httpx2. #1608, #1631

I shipped a quick 0.32.1 fix 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.

Fresh installs of LLM stopped working the other day because the OpenAI Python library dropped its usage of httpx, and it turned out LLM depended on that library but only installed it via a transitive openai dependency.

This dot-release fixes that for the moment by pinning to openai<3, and a soon-to-drop 0.33 release will switch from httpx to httpx2.

Now that this plugin is compatible with LLM 0.32 it can display the reasoning traces for LLMs available through OpenRouter.

• Updated for compatibility with LLM 0.32.
• Models now use OpenRouter's implementation of the Responses API.
• Three new server-side tools: Shell, WebFetch, and WebSearch. Enable these with options like -T WebSearch.

Today saw the long awaited release of Bun 1.4, the first stable version since the infamous Rust rewrite a few months ago.

Interestingly, the Rust rewrite was downplayed in the release notes, which introduced a bewildering array of new features and claimed 2,900 additional bug fixes:

Bun 1.4 adds +1,517 tests from the Node.js test suite - our biggest jump in Node.js compatibility since Bun 1.0. Bun v1.4 also fixes over 2,900 issues. It reduces idle CPU usage by 5x, reduces memory usage by up to 35%, and starts 50% faster on Linux. It adds Bun.Image, Bun.WebView, Bun.markdown, Bun.cron(), Bun.Terminal, bun run --parallel, bun test --parallel, bun audit fix, bun dedupe, and bun prune. And it rewrites Bun from Zig to Rust.

Of these the one that most caught my eye was Bun.WebView, which adds first class support for browser automation to Bun core using either macOS WebKit or control of a local Chromium process via the Chrome DevTools Protocol (CDP).

I had Claude Code for web build a prototype of a web API providing the ability to load a web page and then execute JavaScript against it, inspired by my shot-scraper javascript CLI tool - partly to see how much RAM would be needed by such a service.

Here's that TypeScript server implementation, which appears to need a 192MB-256MB container to run a full Chrome against complex web pages - tested using cgroups.

I tasked Claude Fable 5 running in Claude Code for web with the following research task:

Put https://smolmachines.com through its paces as a fast secure sandbox. Explore what it would take to use this to run untrusted Python and JavaScript code in a way that is limited in what RAM and CPU time it can take up (protection against "while true") with no network access and filesystem access only to designated files

Goal is to be able to use this to execute user-provided tasks for things like data transformations

It quickly ran into a problem: the Claude Code for web environment can't run smol machines. Quoting the notes it wrote:

• This Claude Code container: Linux 6.18.5-fc-v20 (itself a Firecracker guest), 4 vCPU, 15GB RAM. No /dev/kvm, no vmx/svm CPU flags → no nested virt.
• smolvm machine run fails as expected: "kvm not available".
• Plan B: GitHub Actions ubuntu runners DO expose /dev/kvm → run the real test battery via a temporary workflow on this branch, collect logs, remove workflow in final commit.

And Plan B is what it did, installing smolvm and running these tests directly in a GitHub Actions runner against that branch.

That was a creative solution to the environmental limits posed by Claude Code for web. Another example of Fable being relentlessly proactive.

I built this today (with GPT-5.6-Sol xhigh) to help test Qwen 3.8 27B running in LM Studio on both my M5 MacBook Pro and an NVIDIA DGX Spark.

It provides a web UI for exercising an OpenAI-Responses-compatible chat endpoint. I've tried it against LM Studio with the --cors option and OpenRouter, and both work fine.

Conversations are persisted in the browser and can be exported as copy-pasted JSON. One fun detail is that it notices SVG images that are being generated and progressively renders them in the chat while the tokens are still streaming in.