Simon Willison
Bonsai 2 27B: Near-Lossless Compression in a 9x Smaller Footprint
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Simon Willison
Aug 24
llm-anthropic 0.27
The release of llm‑anthropic 0.27 updates the Anthropic plugin for LLM to be compatible with the newly released anthropic v1.0.0 Python library, which has switched from httpx to httpx2. This mirrors a similar change made by OpenAI in their v3.0.0 release two weeks prior. The update includes a migration guide and a pull request that ensures tests pass after upgrading to anthropic>=1.
Simon Willison
Aug 10
Introducing Muse Glimmer
Introducing Muse Glimmer Meta are back in the open weights game! Muse Glimmer is a brand new 30B model under a clean Apache 2.
Simon Willison
Aug 26
Qwen3.8-Flash-Next
Qwen3.8-Flash-Next is an open‑weights multimodal Mixture‑of‑Experts (MoE) model previewing the architecture of Qwen4. It contains 125 B tokens with only 6 B active, giving a performance boost. The author has tested it on a DGX Spark with Unsloth quantized models, exploring variants like UD‑IQ1_S and UD‑Q2_K_XL, and highlighted a high‑reasoning‑effort example from UD‑Q2_K_XL.
Simon Willison
5d ago
pwasm 0.2a0
Release: pwasm 0.2a0 pwasm is one of my folly projects - an entirely vibe-coded pure Python WebAssembly engine that I built in January during my first bout of AI mania. I hadn't touched it sin...
Simon Willison
Sep 7
Video compressor
Simon Willison created a video compressor tool that uses the WebAssembly build of FFMPEG to optimize a demo video of his Equal Earth animation recorded on his phone. He employed Claude Fable 5.1 in Claude Code for web to generate the tool, enabling him to publish the optimized video on his blog. The project showcases how modern web technologies can streamline video processing workflows.
Simon Willison
Sep 2
llm-gemini 0.34
The release of llm-gemini 0.34 introduces the new Gemini 3.8‑Flash model, available in low, medium, and high thinking levels, and fixes an issue where async responses failed to record the resolved model version. The update also notes that Google has released Gemini 3.8‑Flash (and a restricted 3.8 Flash Cyber version) today, with example outputs (pelicans) demonstrating the model’s performance across the different thinking levels. The author highlights Gemini Flash’s speed, low cost, and competence in generating HTML, JavaScript, and Markdown‑SVG content, citing a 13‑second, 1.8‑cent example of an HTML output.