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llama.cpp releases

llama.cpp · b12020

opencl: add fwht (#31434) Co-authored-by: Li He **Website:** - **Attestations:** - **macOS/iOS:** - [macOS Apple Silicon (arm64)](https://github.com/ggml-org/llama.cpp/releases/download/b12020/llama-b12020-bin-macos-arm64.tar.gz) - macOS Apple Silicon (arm64, KleidiAI enabled) [DISABLED](https://github.com/ggml-org/llama.cpp/pull/23780) - [macOS Intel (x64)](https://github.com/ggml-org/llama.cpp/releases/download/b12020/llama-b12020-bin-macos-x64.tar.gz) - [iOS XCFramework](https://github.com/ggml-org/llama.cpp/releases/download/b12020/llama-b12020-xcframework.zip) **Linux:** - [Ubuntu x64 (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/b12020/llama-b12020-bin-ubuntu-x64.tar.gz) - [Ubuntu arm64 (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/b12020/llama-b1202

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llama.cpp releases

llama.cpp · b12019

chat : strip the think block in the qwen3-coder with reasoning_format none (#31380) * chat : accept the think block in the qwen3-coder response format with reasoning_format none Assisted-by: Claude Opus 5.5 * chat : define both qwen3-coder think block variants up front **Website:** - **Attestations:** - **macOS/iOS:** - [macOS Apple Silicon (arm64)](https://github.com/ggml-org/llama.cpp/releases/download/b12019/llama-b12019-bin-macos-arm64.tar.gz) - macOS Apple Silicon (arm64, KleidiAI enabled) [DISABLED](https://github.com/ggml-org/llama.cpp/pull/23780) - [macOS Intel (x64)](https://github.com/ggml-org/llama.cpp/releases/download/b12019/llama-b12019-bin-macos-x64.tar.gz) - [iOS XCFramework](https://github.com/ggml-org/llama.cpp/releases/download/b12019/llama-b12019-xcframework.zip) **Linu

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llama.cpp releases

llama.cpp · b12018

sycl: fix f32 to q2_0/q4_0/q5_0 rounding in CPY (#31120) **Website:** - **Attestations:** - **macOS/iOS:** - [macOS Apple Silicon (arm64)](https://github.com/ggml-org/llama.cpp/releases/download/b12018/llama-b12018-bin-macos-arm64.tar.gz) - macOS Apple Silicon (arm64, KleidiAI enabled) [DISABLED](https://github.com/ggml-org/llama.cpp/pull/23780) - [macOS Intel (x64)](https://github.com/ggml-org/llama.cpp/releases/download/b12018/llama-b12018-bin-macos-x64.tar.gz) - [iOS XCFramework](https://github.com/ggml-org/llama.cpp/releases/download/b12018/llama-b12018-xcframework.zip) **Linux:** - [Ubuntu x64 (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/b12018/llama-b12018-bin-ubuntu-x64.tar.gz) - [Ubuntu arm64 (CPU)](https://github.com/ggml-org/llama.cpp/releases/download/b12018/ll

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SiliconANGLE AI

Google, Anthropic and others to support new AI crawling opt-out standard

Google LLC, Microsoft Corp., Anthropic PBC and OpenAI Group PBC today announced plans to support an upcoming website crawling standard. The technology will enable website operators to block artificial intelligence developers from using their content to train their models. Many websites contain a text file titled “robots.txt” that informs crawlers what content they may access. […] The post Google, Anthropic and others to support new AI crawling opt-out standard appeared first on SiliconANGLE.

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Tencent News · AI Channel

China‑bound Apple Intelligence enters beta testing in 4 days! Alibaba officially announces full integration of Qwen.

Author: Li Shuiqing | Editor: Xin Yuan — According to Zhidongxi (WeChat official account: zhidxcom), on October 31, Alibaba announced a partnership with Apple to integrate Qwen into Apple Intelligence. Chinese users will be able to directly access Qwen’s capabilities for text and image understanding, content generation, and more, within Siri, writing tools, and visual intelligence features. These functions will begin beta testing starting November 4 alongside the latest iOS Developer Beta version, and...

国行苹果智能倒计时4天开测！阿里官宣，千问全面接入
AITencent News
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Simon Willison

dbreunig/nesformer

dbreunig/nesformer Inspired by qwenputer by Divyansh Agrawal, Drew Breunig baked a working emulator for a Nintendo Entertainment System 6502 CPU into the weights of Qwen3.5-4B. You can now play NES ROMs such as Super Mario Bros (very slowly) running inside Qwen! In a comment on Hacker News Drew reveals the Opus 5.5 prompts he used to build this system: Read this article and any relevant source code: https://divagr.com/blog/qwenputer. Then explore if you could emulate the chip and ram in a Nintendo Entertainment System (as people do today with FPGAs in MISTRs) using this technique. If so, what size model would you have to build and if you could use smaller faster ones, could you get it to be at the standard clockspeed. Followed by: I think we should build it! Just for fun. It's okay if it's

Individual
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AWS Machine Learning Blog

Preview web apps live as your coding agent builds them with Amazon Bedrock AgentCore runtime

Amazon Bedrock AgentCore Session endpoints give each runtime session an authenticated URL that forwards any HTTP method, path, and WebSocket connection to the ports you allow. In this post, you deploy a coding agent that keeps a Vite website running in its session, then watch the live site update in your browser as the agent edits files.

OfficialTutorials
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