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Tag: model support

  • Simon Willison’s Weblog: Four new releases from Qwen

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    Kurt Seifried
    in

    Source URL: https://simonwillison.net/2025/Sep/22/qwen/ Source: Simon Willison’s Weblog Title: Four new releases from Qwen Feedly Summary: It’s been an extremely busy day for team Qwen. Within the last 24 hours (all links to Twitter, which seems to be their preferred platform for these announcements): Qwen3-Next-80B-A3B-Instruct-FP8 and Qwen3-Next-80B-A3B-Thinking-FP8 – official FP8 quantized versions of their Qwen3-Next models.…

  • Simon Willison’s Weblog: Locally AI

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    Kurt Seifried
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    Source URL: https://simonwillison.net/2025/Sep/21/locally-ai/ Source: Simon Willison’s Weblog Title: Locally AI Feedly Summary: Locally AI Handy new iOS app by Adrien Grondin for running local LLMs on your phone. It just added support for the new iOS 26 Apple Foundation model, so you can install this app and instantly start a conversation with that model without…

  • Cloud Blog: Achieve agentic productivity with Vertex AI Agent Builder

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    Kurt Seifried
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    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/get-started-with-vertex-ai-agent-builder/ Source: Cloud Blog Title: Achieve agentic productivity with Vertex AI Agent Builder Feedly Summary: Enterprises need to move from experimenting with AI agents to achieving real productivity, but many struggle to scale their agents from prototypes to secure, production-ready systems.  The question is no longer if agents deliver value, but how to…

  • Docker: Build and Distribute AI Agents and Workflows with cagent

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    Kurt Seifried
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    Source URL: https://www.docker.com/blog/cagent-build-and-distribute-ai-agents-and-workflows/ Source: Docker Title: Build and Distribute AI Agents and Workflows with cagent Feedly Summary: cagent is a new open-source project from Docker that makes it simple to build, run, and share AI agents, without writing a single line of code. Instead of writing code and wrangling Python versions and dependencies when creating…

  • Cloud Blog: Google Cloud’s open ecosystem for Apache Iceberg

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    Kurt Seifried
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    Source URL: https://cloud.google.com/blog/products/data-analytics/committing-to-apache-iceberg-with-our-ecosystem-partners/ Source: Cloud Blog Title: Google Cloud’s open ecosystem for Apache Iceberg Feedly Summary: AI is transforming data into a strategic asset, driving demand for flexible, integrated, and real-time data architectures. But yesterday’s data tools can’t handle AI’s demand for massive volumes of real-time and multi-modal data. Data lakes, for instance, offer flexibility…

  • Simon Willison’s Weblog: OpenAI’s new open weight (Apache 2) models are really good

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    Kurt Seifried
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    Source URL: https://simonwillison.net/2025/Aug/5/gpt-oss/ Source: Simon Willison’s Weblog Title: OpenAI’s new open weight (Apache 2) models are really good Feedly Summary: The long promised OpenAI open weight models are here, and they are very impressive. They’re available under proper open source licenses – Apache 2.0 – and come in two sizes, 120B and 20B. OpenAI’s own…

  • Cloud Blog: Announcements for AI Hypercomputer: The latest infrastructure news for ML practitioners

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    Kurt Seifried
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    Source URL: https://cloud.google.com/blog/products/ai-machine-learning/q2-2025-ai-hypercomputer-updates/ Source: Cloud Blog Title: Announcements for AI Hypercomputer: The latest infrastructure news for ML practitioners Feedly Summary: Curious about the latest in AI infrastructure from Google Cloud? Every three months we share a roundup of the latest AI Hypercomputer news, resources, events, learning opportunities, and more. Read on to learn new ways…

  • Simon Willison’s Weblog: Trying out Qwen3 Coder Flash using LM Studio and Open WebUI and LLM

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    Kurt Seifried
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    Source URL: https://simonwillison.net/2025/Jul/31/qwen3-coder-flash/ Source: Simon Willison’s Weblog Title: Trying out Qwen3 Coder Flash using LM Studio and Open WebUI and LLM Feedly Summary: Qwen just released their sixth model(!) for this July called Qwen3-Coder-30B-A3B-Instruct – listed as Qwen3-Coder-Flash in their chat.qwen.ai interface. It’s 30.5B total parameters with 3.3B active at any one time. This means…