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    <title>Qwen on KAD</title>
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    <description>Recent content in Qwen on KAD</description>
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      <title>ClawBench Exposes the Limits of AI Agents on the Real Web</title>
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      <pubDate>Wed, 02 Sep 2026 22:43:14 +0800</pubDate>
      
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&lt;p&gt;ClawBench Exposes the Limits of AI Agents on the Real Web&lt;/p&gt;&lt;/blockquote&gt;
&lt;p&gt;If AI agents appear ready to book flights, submit expense reports, order food, or apply for jobs on your behalf, &lt;strong&gt;ClawBench&lt;/strong&gt; offers a sobering reality check.&lt;/p&gt;</description>
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      <title>Alibaba XuanTie C950 Runs 27B Qwen Model at 30 Tokens/s</title>
      <link>https://www.kad8.com/ai/alibaba-xuantie-c950-runs-27b-qwen-model-at-30-tokens-per-second/</link>
      <pubDate>Wed, 19 Aug 2026 22:24:58 +0800</pubDate>
      
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&lt;p&gt;Alibaba XuanTie C950 Runs 27B Qwen Model at 30 Tokens/s&lt;/p&gt;&lt;/blockquote&gt;
&lt;p&gt;Alibaba&amp;rsquo;s &lt;strong&gt;XuanTie C950&lt;/strong&gt; RISC-V processor is emerging as an unusual alternative to GPU-based AI inference. The 64-core chip can reportedly run Alibaba&amp;rsquo;s &lt;strong&gt;27-billion-parameter Qwen model natively on the CPU&lt;/strong&gt;, without requiring a discrete GPU or a translation layer.&lt;/p&gt;</description>
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      <title>PrismML Bonsai 27B Brings Local AI Models to iPhone-Class Hardware</title>
      <link>https://www.kad8.com/ai/prismml-bonsai-27b-brings-local-ai-models-to-iphone-class-hardware/</link>
      <pubDate>Wed, 15 Jul 2026 17:29:25 +0800</pubDate>
      
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&lt;p&gt;PrismML Bonsai 27B Brings Local AI Models to iPhone-Class Hardware&lt;/p&gt;&lt;/blockquote&gt;
&lt;p&gt;PrismML has introduced &lt;strong&gt;Bonsai 27B&lt;/strong&gt;, a compressed large language model (LLM) that the company claims can run entirely on an iPhone 17 Pro equipped with 12GB of memory. If these claims withstand independent validation, the release could represent a significant milestone for on-device AI, demonstrating that models previously reserved for high-memory desktop systems can be deployed on consumer smartphones.&lt;/p&gt;</description>
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