Simon Willison introduces Hy4 Preview, a new large language model from Tencent featuring 770 B total parameters, 49 B active parameters, a 1 M token context window, and 1.56 TB of storage on Hugging Face. The release marks a significant increase over Hy3, which had 295 B total parameters, 21 B active parameters, a 256 k token context window, and 598 GB of storage. Willison also shares the model’s chat template, highlighting two reasoning effort levels—‘high’ (default) and ‘no_think’—and demonstrates a sample prompt that showcases the model’s reasoning trace.
whyItMatters":"The article provides concrete details on Hy4’s scale and configuration, illustrating Tencent’s advancement in large‑language‑model capabilities and offering practical insights into its usage through the chat template and reasoning settings."
Simon Willison announces the release of the llm-openai-decisions 0.1a0 plugin, which interfaces with OpenAI’s new Jev-style Decisions API. The plugin, inspired by llm-typesafe, supports image and text input and offers the same three question types (yes/no, choices, scores) as Jev, with pricing at 10¢ per million input tokens. Installation is simple via `llm install llm-openai-decisions`, and an example query demonstrates image-based evaluation.
The article discusses a shift in code review practices, moving from a final gate to continuous review that functions like spellcheck during coding. It highlights how the Claude Code team uses the Claude AI to catch routine mistakes before human reviewers intervene, allowing developers to focus on higher-level issues. The piece references insights from Addy Osmani, Morgan Westlee Lunt, and Qing Wang on this evolving approach.
Release: llm-openrouter 0. 7 Now that this plugin is compatible with LLM 0.
The article announces that Claude Code will now support AGENTS.md files starting with version 2.1.277. If a CLAUDE.md file is absent in a folder, Claude will automatically look for and use AGENTS.md, leveraging Claude Code mods to customize the harness. The built‑in mod is available for use, and users can also create their own custom project instructions.
The release of llm 0.36 introduces new OpenAI models gpt-6-sol and gpt-6-luna, and adds support for model plugins to declare that they do not support conversations via supports_conversation = False. When such models receive assistant or tool history, llm raises a ConversationNotSupported error and the chat interface rejects them before starting a session. Additional changes include wrapping reasoning traces in Markdown output with <details> tags and bug fixes from five contributors.
Posted by Zheng Xu, Research Scientist, and Yanxiang Zhang, Software Engineer, Google Language models (LMs) trained to predict the next word given input text are the key technology for many applications [ 1 , 2 ]. In Gboard , LMs are used to improve users’ typing experience by supporting features like next word prediction (NWP), Smart Compose , smart completion and suggestion , slide to type , and proofread .
By Google AI
But then users start to report a weird bug. It's the 4th time your team has been trying to fix it.
Stealing Reasoning Traces from Proprietary LLM APIs A vanity domain name ( stolen-thoughts. com ) for a neat paper : Anthropic, OpenAI, and Google return encrypted chain-of-thought blocks to clients that can be replayed across sessions, users, and models.
The release of llm 0.34 introduces a new feature that enhances log output by including response duration in both milliseconds and a human‑readable format. The short log view now contains a dedicated duration_ms field. Additionally, the update incorporates multiple bug fixes and a notable performance boost to llm logs, attributed to waveplate integration.
Simon Willison has released the September edition of his sponsors‑only monthly newsletter. The issue covers new Fable class models, a pricing war, 3D graphics with Blender and pixel art, LLMs applied to mathematics, accidental cyberattacks, the vulnapocalypse affecting Datasette, his current tools, and software releases for 2026. Sponsors can access the full newsletter for $10/month, with an August preview available for free.
The article announces the release of llm-echo version 0.5, a debug plugin that simulates an LLM by echoing back prompts without actual model inference. The new version updates token usage calculations to include tool calls, system prompts, and reasoning tokens. An example shows how to invoke the plugin and view the resulting prompt and token usage.