LLM 0.32 adds agent hooks, LFM2.5 matches a 120B teacher, MiniMax-H3 hits M5 Max

Sources

New release of LLM adds support for reasoning traces, OpenAI Responses, server-side tools, and smarter logging simonwillison.net

I released LLM 0.32 this morning, the most significant new version of LLM since the initial launch of the project. The new version includes support for visible reasoning traces, server-side provider tools, redesigned content-addressable SQLite logs, new models, and new features enabled by the OpenAI Responses API. I also released a new version of the llm-anthropic plugin with substantial updates of its own. Headline features for LLM CLI users Running LLM against reasoning models now displays th…

llm-anthropic 0.26 simonwillison.net

Release: llm-anthropic 0.26 Includes new features enabled by LLM 0.32 : New models: claude-fable-5 , claude-sonnet-5 , and claude-opus-5 . #75 , #76 Added server-side tools for WebSearch , WebFetch , CodeExecution , and AnthropicMCP , available through LLM’s -T interface or Python tools= . The previous -o web_search* options have been removed in favor of -T WebSearch . #79 Upgraded to llm>=0.32 . Reasoning, tool calls, tool results, and server-side tool results now stream as typed events. Reaso…

llm 0.32 simonwillison.net

Release: llm 0.32 See my detailed blog post about this release . Tags: llm

Deploy local agents everywhere with LFM2.5-2.6B huggingface.co

PipeNetwork/minimax-h3-mlx simonwillison.net

PipeNetwork/minimax-h3-mlx MiniMax released MiniMax-H3 two days ago - they describe it as a “a general-purpose, omni-modal generative system”, which in practice means it accepts text, images, audio and video and can use them to generate up to 15 second video clips with audio included. This Python package ports it to MLX for running on Apple Silicon. I got it running on my M5 Max MacBook Pro. I cloned the repo and ran the model like this: # First download the models uvx —from huggingface_hub hf…

Unpacking ChatGPT Work: the Agent for a Billion Users latent.space

ChatGPT Work, OpenAI’s enterprise agent aimed at a billion users, gets an external teardown covering seven subsystems: Memory, Proactivity, Scheduling, Browser Use, Plugins, Skills and Tools. The reconstruction maps how each piece interoperates, giving builders a reference architecture for agent-style products beyond the marketing surface.

(AINews) Megakernels are so dead and so back latent.space

Megakernels — the single-kernel-per-model GPU compilation trick once written off — resurface in an engineering debate paired with a fresh Cursor launch. The pattern trades scheduler overhead for compile complexity, and its revival signals renewed appetite for squeezing latency out of inference stacks.

condense-json 1.1 simonwillison.net

The JSON-shrinking library from Simon Willison follows its 1.0 release with non-string replacement values and merge-based diffs between similar objects, letting condense_json store key updates and deletions. Hypothesis-powered round-trip property tests now guard the encode/decode symmetry.

References

Anthropic — Claude Opus 5 announcement anthropic.com

Opus 5 topped Zapier’s AutomationBench with a 100% pass rate, effectively managing multi-step business workflows that previous models failed

r/ClaudeAI — ‘Opus 5 extremely RL-fried and mistake-prone’ reddit.com

Opus 5 acts like an ‘eager junior dev,’ showing overconfidence and occasional ‘amnesia’ by performing actions (like commenting out critical code) and then forgetting it did so

developersdigest.tech — Best CLI Tools for AI Development 2026 developersdigest.tech

Compromised PyPI versions (v1.82.7–8) were found to exfiltrate SSH keys and cloud secrets, leading many enterprise teams to migrate toward compiled, more secure alternatives like Bifrost or Kong AI Gateway

mgks.dev — ‘Datasette Agent: when three years of tooling finally converge’ mgks.dev

shifts value away from the specific model used and into the ‘plugin and data access layer,’ allowing developers to arbitrage between different LLM providers based on price and performance

jatinbansal.com — ‘The Agent Loop’ jatinbansal.com

The ‘driver’ (the code running the agent) provides the model with a context of conversation history and tool schemas; the model then emits tool calls, which the driver executes

dev.to — ‘Coding CLIs in mid-2026: the engineer’s map’ dev.to

developers frequently start with 7+ tools but eventually consolidate to a minimal stack consisting of one IDE, one terminal agent (aider), and one gateway

Distil Labs writeup via r/neuralnetworks reddit.com

out-of-the-box multi-turn tool calling is ‘sloppy’—yielding only 34–63% accuracy—[but] exceptionally responsive to task-specific fine-tuning… After just one epoch of SFT, the model reached 96–98% tool call equivalence, effectively matching the performance of a 120B teacher model

Liquid AI LFM Open License v1.0 docs docs.liquid.ai

Organizations generating less than [$10M USD annual revenue] are granted broad, royalty-free rights… Once a legal entity or its affiliates exceed this revenue cap, the right to use the model for ‘direct or indirect commercial advantage’ under the open license terminates automatically

LFM2.5-2.6B Hugging Face model card huggingface.co

native ‘Pythonic’ tool-calling format wraps function calls in specialized and tokens… parsers in Ollama and llama.cpp often fail to recognize these tokens, displaying them as raw text or triggering server errors

VentureBeat on LFM2-350M venturebeat.com

Liquid AI’s smallest model yet, LFM2-350M, beats models 4x its size at data extraction, can run anywhere — a pattern the company has repeated with the 2.6B release aimed at agentic tool use

XDA Developers hands-on comparison xda-developers.com

tested Gemma 4, Qwen 3.5, Ministral 3 for vision tasks — only one understood the assignment… advertised benchmark parity does not always translate to reliable real-world behavior on constrained hardware

AI Weekly newsletter aiweekly.co

Liquid AI ships LFM2.5-2.6B, a phone-ready agent model… 220 tokens/s on Apple M5 Max, under 2.5 GB memory, positioned as a private on-device alternative eliminating per-token cloud costs

RunPod blog — ‘MiniMax-H3: the open-weight omni-modal video model and what it takes to run it’ runpod.io

The MiniMax H3 Community License specifically excludes use in the United States, United Kingdom, European Union, and South Korea… the downloadable H3-Base model only supports 768p resolution; native 2K relies on a proprietary H3-Regenerate-2K stage that remains closed-source and accessible only via the company’s paid API.

Evolink.ai — Hailuo 3 API guide evolink.ai

2K API output is priced at roughly $0.13 per second, approximately one-twelfth the cost of ByteDance’s Seedance 2.5… documentation mandates a rigid 5-block structure: Subject, Action, Environment, Camera, and a dedicated Sound/Ending block.

Hugging Face blog — ResterChed, ‘MiniMax H3 / Hailuo 3.0’ review huggingface.co

By pruning ‘modulation weights’ (~40% of parameters) into a lookup table, engineers shrunk the memory footprint from 123GB to roughly 42GB without loss in quality, allowing the model to fit on consumer GPUs like the RTX 3060.

Trilogy AI Substack — MiniMax H3 review trilogyai.substack.com

Accurate speech says nothing about the accuracy of the pictures behind it… the model may produce perfectly synced speech for a character whose anatomy is ‘absurd’ or whose physical surroundings melt during the shot; it frequently loses subject identity by the fourth shot in a sequence — a failure mode dubbed the ‘Shot-4 Test’.

Arena.ai text-to-video leaderboard arena.ai

Wan 2.2 is released under the permissive Apache 2.0 license, allowing unrestricted commercial use… MiniMax-H3, while marketed as ‘open-weight,’ uses a more restrictive Community License… its most advanced ‘In-Context Regeneration’ features are currently locked behind a serverless API.

Hugging Face discussion #12 on MiniMaxAI/MiniMax-H3 huggingface.co

Enabling —use-sage-attention causes the 8-bit model to produce ‘pure noise’ rather than a coherent signal… the H3 Diffusion Transformer fails to route low-precision attention calls correctly; users report thermal peaks up to 83°C and system crashes after ~14 minutes of generation.