Meet WebBrain: An Open-Source, Local-First AI Browser Agent That Reads Pages and Automates Tasks in Chrome and Firefox

We’ve compiled an overview of some of the top alternative browsers available today aiming to challenge Chrome and Safari.

Liquid AI released LFM2.5-230M, its smallest model yet. The 230M-parameter, open-weight model runs on-device at 213 tok/s on a Galaxy S25 Ultra and 42 on a Raspberry Pi 5. Built on the LFM2 architecture, it targets tool use and data extraction, beating larger models like Qwen3.5-0.8B and Gemma 3 1B on instruction following. The post Liquid AI Ships LFM2.5-230M with llama.cpp, MLX, vLLM, SGLang, and ONNX Support for On-Device Inference appeared first on MarkTechPost.

Meta released Astryx, an open-source React design system built on StyleX. It pairs a CSS-variable theme cascade with a CLI and MCP server, so both engineers and AI agents build using the same API. The project is in Beta, MIT-licensed, and grew inside Meta over eight years. The post Meta’s Astryx Brings a CLI and MCP Server to an Open-Source React Design System Agents Can Read appeared first on MarkTechPost.

Using Gemma 4, Ollama, OpenAI Agents SDK, and Tavily MCP to build a lightweight research agent The post From Local LLM to Tool-Using Agent appeared first on Towards Data Science.

From installing Ollama to launching OpenCode with a local model, step by step. The post Build Your Own Local AI Coding Agent with Gemma 4 and OpenCode appeared first on Towards Data Science.

A banking malware that is “well-camouflaged” and “nearly invisible” to cyber threat detection systems is on the loose in Latin America, according to tech giant IBM. Senior threat researcher Itzhak Chimino says IBM uncovered a banking trojan known as UnregStealer that is targeting Latin American banks while posing as a Chrome browser extension. According to […] The post IBM Issues Warning on ‘Well-Camouflaged’ Bank Malware That’s Draining Login Credentials appeared first on The Daily Hodl.

Z.ai has released GLM-5.2, an MIT-licensed open-source AI model designed for long-running software engineering tasks, as the Chinese company seeks to challenge proprietary coding models on cost and performance. The company said GLM-5.2 ranked just behind Anthropic’s Claude Opus 4.8 on FrontierSWE, a long-horizon coding benchmark, trailing it by 1%. Z.ai said the model also edged out OpenAI’s GPT-5.5 by 1%. Z.ai said GLM-5.2 supports a one-million-token context window with up to 131,072 output tokens, positioning it for agentic coding workflows that require reasoning across large codebases. The company is also making an efficiency argument. It said GLM-5.2 uses a technique called IndexShare, which reduces per-token compute by 2.9 times at a one-million-token context length. It also said changes to the model’s multi-token prediction layer increased the acceptance length for speculative decoding by up to 20%. The changes are aimed at a practical problem for developers: long-context coding

Z.ai has released GLM-5.2, an MIT-licensed open-source AI model designed for long-running software engineering tasks, as the Chinese company seeks to challenge proprietary coding models on cost and performance. The company said GLM-5.2 ranked just behind Anthropic’s Claude Opus 4.8 on FrontierSWE, a long-horizon coding benchmark, trailing it by 1%. Z.ai said the model also edged out OpenAI’s GPT-5.5 by 1%. Z.ai said GLM-5.2 supports a one million-token context window with up to 131,072 output tokens, positioning it for agentic coding workflows that require reasoning across large codebases. The company is also making an efficiency argument. It said GLM-5.2 uses a technique called IndexShare, which reduces per-token compute by 2.9 times at a one million-token context length. It also said changes to the model’s multi-token prediction layer increased the acceptance length for speculative decoding by up to 20%. The changes are aimed at a practical problem for developers: long-context coding