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    <title>iqshard Dev Log</title>
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    <description>What got built, what got decided, and what is still unresolved.</description>
    <language>en</language>
    <lastBuildDate>Wed, 23 Sep 2026 16:29:45 GMT</lastBuildDate>
    <item>
      <title>Kimi K3 vs GLM-5.3: The Scoreboard Isn’t the Verdict</title>
      <link>https://www.iqshard.com/dev-log/kimi-k3-vs-glm-5-3</link>
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      <pubDate>Tue, 25 Aug 2026 00:00:00 GMT</pubDate>
      <description>Scorecards give Kimi K3 the edge over GLM-5.3. Matched metrics, independent evals, and finished-task costs tell a more useful story for anyone building software.</description>
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    <item>
      <title>GLM-5.3 Just Shipped, and It Is Not a Small Update</title>
      <link>https://www.iqshard.com/dev-log/glm-5-3</link>
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      <pubDate>Sat, 15 Aug 2026 00:00:00 GMT</pubDate>
      <description>GLM-5.3 is a post-training-only upgrade that nearly doubles AutomationBench, more than doubles ExploitBench, and closes the gap to GPT-5.6 Sol on agentic coding.</description>
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    <item>
      <title>Why More Context Doesn&apos;t Mean Better Answers</title>
      <link>https://www.iqshard.com/dev-log/better-context-not-more-context</link>
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      <pubDate>Thu, 23 Jul 2026 00:00:00 GMT</pubDate>
      <description>A large context window tells you how much a model can accept, not how much it can use well. Better answers come from smaller, targeted context</description>
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      <title>Kimi K3: Open Weights Reach the Frontier</title>
      <link>https://www.iqshard.com/dev-log/kimi-k3</link>
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      <pubDate>Fri, 17 Jul 2026 00:00:00 GMT</pubDate>
      <description>Moonshot AI releases Kimi K3 with full open weights — a 2.8T-parameter MoE with native vision and a 1M-token context, and the closest an open model has come to the closed frontier.</description>
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      <title>Why an Agent Uses Far More Tokens Than a Chatbot</title>
      <link>https://www.iqshard.com/dev-log/agent-vs-chatbot-cost</link>
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      <pubDate>Fri, 19 Jun 2026 00:00:00 GMT</pubDate>
      <description>A chatbot and an agent run on the same kind of model and the same tools. What makes an agent burn far more tokens is not how it works, but what it is for</description>
    </item>
    <item>
      <title>GLM-5.2: Built for Long-Horizon Work</title>
      <link>https://www.iqshard.com/dev-log/glm-5-2</link>
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      <pubDate>Wed, 17 Jun 2026 00:00:00 GMT</pubDate>
      <description>GLM-5.2 holds a stable 1M-token context and leads open-weights models on long-horizon, tool-using work — the kind of work that resembles a real job.</description>
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    <item>
      <title>Input, Output, Cached: The Three Kinds of Token in a Request</title>
      <link>https://www.iqshard.com/dev-log/token-types</link>
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      <pubDate>Tue, 02 Jun 2026 00:00:00 GMT</pubDate>
      <description>A request is made of three kinds of token — input, output, and cached — and each is handled differently. How they work, and why caching reuses text across users</description>
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    <item>
      <title>Three Variations on the Leaky Bucket: Queue, Meter, and Token Budget</title>
      <link>https://www.iqshard.com/dev-log/leaky-bucket</link>
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      <pubDate>Mon, 25 May 2026 00:00:00 GMT</pubDate>
      <description>Three rate-limiter designs apply the same leaky-bucket concept as a queue, an activity meter, or a replenishing token budget.</description>
    </item>
    <item>
      <title>What Exactly Are Tokens?</title>
      <link>https://www.iqshard.com/dev-log/what-are-tokens</link>
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      <pubDate>Fri, 22 May 2026 00:00:00 GMT</pubDate>
      <description>Tokens are how AI models read and write, and how you are charged. A plain guide to input, output, and cached tokens for people who sign the invoices</description>
    </item>
    <item>
      <title>The NVIDIA DGX B300: An AI Factory in Ten Rack Units</title>
      <link>https://www.iqshard.com/dev-log/dgx-b300</link>
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      <pubDate>Wed, 29 Jul 2026 00:00:00 GMT</pubDate>
      <description>Eight Blackwell Ultra GPUs, 2.304 TB of HBM3e, and NVLink stitching eight accelerators into one very large GPU — inside the NVIDIA DGX B300.</description>
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