Release: llm-gemini 0. 33 It's been a while since the last llm-gemini release.
Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at Simon Willison.
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.
Simon Willison tested GPT‑6 Astra by generating SVG pelicans riding bicycles at various reasoning levels and compared the results to GPT‑5.6 Sol, Terra, and Luna. The Astra pelicans consistently outperformed the other models, especially at low and xhigh reasoning levels, and even the Astra max version produced high‑quality images. Astra also used fewer tokens and was roughly twice as expensive as Sol, yet its low‑level output was cheaper and superior to any Sol model.
Simon Willison introduces GPT‑6 Astra, a new model that offers improved attention to detail, better prompt comprehension, and the ability to generate more sophisticated outputs. The model excels at creating 3D renderings, producing detailed scenes such as gardens, shipyards, animals, cityscapes, and even Dyson spheres. Willison highlights its whimsical creativity, noting examples like a pelican wearing a red neckerchief riding a bicycle.
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.
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 announces the release of ChatGPT Images 2.5, noting that OpenAI’s image generation models have processed over 3 billion images across ChatGPT Images and the GPT‑Image API. The new version improves instruction‑following across multiple turns, speeds up responses, and better preserves subjects from reference photos. Two new API model IDs—gpt‑image‑2.5‑sunburst and gpt‑image‑2.5‑flare—are available, with Sunburst recommended for precision editing and Flare for fast, high‑quality everyday generation. Willison has updated his openai_image.py CLI tool to accept reference images, demonstrating its use with a raccoon scientist prompt.