Muse Spark Open is Meta’s newly released open-weight AI model, announced on October 15, 2026. With 816 billion total parameters, 42 billion active parameters and a context window of 1,048,576 tokens, Muse Spark Open is designed for coding agents, long-running software engineering tasks and multimodal reasoning. The release makes the model weights available to developers, […]
Voyager, a new desktop “open harness for creative work” from the makers of Moda, launched on 8 October for Apple Silicon Macs. Its agent, powered by your own Claude or ChatGPT subscription, Claude Opus, GPT-6.1 Sol or cheap open-weight models such as DeepSeek, drives After Effects, DaVinci Resolve, Blender, Unity and Ableton and ships free design, video and music engines. We cover how it works, the models, plans and credits, the Claude Code plugin, requirements and privacy.
Musubi’s open-weights PolicyLM-1.7B brings the decision-model idea behind Jev to AI content moderation: it reads your own policy and scores every message in tens of milliseconds. We explain how it works, what the benchmarks really show, where it falls short, and how to pilot it under UK and EU rules.
AIxploria’s new Mistral Large 4 card invites readers to discover Mistral’s trillion-parameter model. We check its twelve claims against Mistral’s announcement and Artificial Analysis: the technical summary holds up, but the open-source label is premature, the Free tag is wrong and the #27 badge belongs to Claude Sonnet 5.
Mistral Large 4 scored 38.4 on the Artificial Analysis Intelligence Index: sixth among the open-weight models on the launch chart, eighth on the full leaderboard and first outside China. We show every way of counting, the sub-scores against MiMo, GLM and DeepSeek, cost and time per task, and what could move it.
Mistral has released Mistral Large 4, a 1-trillion-parameter open-weight model with 49 billion active parameters, as a preview, with weights due by the end of October. We cover the specs, the sovereign AI pitch, the cyber defence claims, independent rankings, price per task, self-hosting memory and the licence question.
Four TechCrunch Disrupt 2026 sessions, from Together AI, CapitalG and Pathway to Oumi, Nvidia and Ricursive Intelligence, tackle how founders choose between frontier APIs and open-weight models. We explain what open and closed really mean, what Menlo Ventures’ data and current list prices show, and give a five-question framework for deciding what to rent, customise or own.
From 9 October 2026, free Gemini app users on personal accounts are limited to Flash-Lite, AI Plus loses Pro, and AI Pro gains Deep Think. We set out the new model table with UK prices, context windows and limits, why Google is rationing its best models, and how Aleph Alpha’s open-weight Kolibri-1 offers the opposite: a model you download and keep.
Aleph Alpha has released Kolibri, an English and German mixture-of-experts model with 78.1 billion parameters, 3.46 billion active per token, open weights under Apache 2.0 and up to 1M tokens of context. It was trained to 262,144 tokens and reaches a million by extrapolation. We cover the architecture, the long-context scores, benchmarks against Qwen, Nemotron and Mistral, hardware needs, the licence and the Cohere merger.
Black Forest Labs chief executive Robin Rombach told AFP that Europe must swap “risk and fear” for optimism about AI, just as the industry’s safety debate peaks. We profile the Freiburg maker of FLUX, test its claim that open-weight models are safer against its own red-team figures, measure Europe’s capital gap with official data, and cover the EU AI Act changes, the Audi robot trials and the Scorsese row.
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