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  <title>Low Budget Lab</title>
  <link>https://lowbudgetlab.com/</link>
  <description>Real experiments with local AI on low-budget hardware</description>
  <language>en</language>
  <item>
    <title>Why I wrote my own inference engine for two P100s</title>
    <link>https://lowbudgetlab.com/posts/p100-own-inference-engine/</link>
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    <pubDate>Sun, 25 Oct 2026 00:00:00 GMT</pubDate>
    <description>Patching llama.cpp got a 27B model to 32 tok/s on two P100s. A from-scratch CUDA engine built for just this card and model reached 49 tok/s plain and about 118 tok/s with the model's own draft head.</description>
  </item>
  <item>
    <title>P100 power caps, clocks and cooling: what the numbers say</title>
    <link>https://lowbudgetlab.com/posts/p100-power-and-cooling/</link>
    <guid isPermaLink="true">https://lowbudgetlab.com/posts/p100-power-and-cooling/</guid>
    <pubDate>Sun, 25 Oct 2026 00:00:00 GMT</pubDate>
    <description>The P100 is a passive 250 W card. What a 125, 150 and 250 W cap does to its clocks and temperatures, why nvidia-smi -lgc fails on Pascal, and the fan mistake that let both cards hit 79 °C.</description>
  </item>
  <item>
    <title>Beyond chat: video generation and fine-tuning on two P100s</title>
    <link>https://lowbudgetlab.com/posts/p100-video-and-fine-tuning/</link>
    <guid isPermaLink="true">https://lowbudgetlab.com/posts/p100-video-and-fine-tuning/</guid>
    <pubDate>Sun, 25 Oct 2026 00:00:00 GMT</pubDate>
    <description>Two P100s can make a short AI video clip and can fine-tune a 27B model. Both work. Neither beats a single RTX 3070 for video, and fine-tuning is measured in days.</description>
  </item>
  <item>
    <title>Securing a local AI agent: best practices</title>
    <link>https://lowbudgetlab.com/posts/securing-a-home-ai-agent/</link>
    <guid isPermaLink="true">https://lowbudgetlab.com/posts/securing-a-home-ai-agent/</guid>
    <pubDate>Sun, 25 Oct 2026 00:00:00 GMT</pubDate>
    <description>An agent that can read your mail, run commands and browse the web needs more than a good prompt. Ten practices for the tool layer, where the real risk is, plus a checklist.</description>
  </item>
  <item>
    <title>Two P100s in one Ubuntu box: driver 580, CUDA 12.9 and the IOMMU trap</title>
    <link>https://lowbudgetlab.com/posts/two-p100s-ubuntu/</link>
    <guid isPermaLink="true">https://lowbudgetlab.com/posts/two-p100s-ubuntu/</guid>
    <pubDate>Sun, 25 Oct 2026 00:00:00 GMT</pubDate>
    <description>Moving both P100s into one Ubuntu 26.04 machine. The setup was easy except for one thing: GPU-to-GPU copies ran at 0.14 GB/s until I changed one kernel setting.</description>
  </item>
  <item>
    <title>Stretching context to 500K on 8 GB cards, and why I backed it out</title>
    <link>https://lowbudgetlab.com/posts/long-context-small-cards/</link>
    <guid isPermaLink="true">https://lowbudgetlab.com/posts/long-context-small-cards/</guid>
    <pubDate>Sun, 27 Sep 2026 00:00:00 GMT</pubDate>
    <description>YaRN makes huge context windows easy to turn on. On small cards it's the KV cache, not the setting, that decides whether it works.</description>
  </item>
  <item>
    <title>Pairing a P100 with a gaming GPU: splits, buffers and the small-card trap</title>
    <link>https://lowbudgetlab.com/posts/p100-pairing-gaming-gpu/</link>
    <guid isPermaLink="true">https://lowbudgetlab.com/posts/p100-pairing-gaming-gpu/</guid>
    <pubDate>Sun, 27 Sep 2026 00:00:00 GMT</pubDate>
    <description>How to split one model across a 16 GB P100 and an 8 GB RTX 3070, and why the smaller card sets every limit.</description>
  </item>
  <item>
    <title>CUDA 13 and PyTorch dropped the P100: what still works</title>
    <link>https://lowbudgetlab.com/posts/p100-software-2026/</link>
    <guid isPermaLink="true">https://lowbudgetlab.com/posts/p100-software-2026/</guid>
    <pubDate>Sun, 27 Sep 2026 00:00:00 GMT</pubDate>
    <description>'No kernel image is available for execution on the device.' Here's which llama.cpp and PyTorch builds still run on sm_60.</description>
  </item>
  <item>
    <title>Is a used Tesla P100 worth it for local LLMs in 2026?</title>
    <link>https://lowbudgetlab.com/posts/p100-worth-it-2026/</link>
    <guid isPermaLink="true">https://lowbudgetlab.com/posts/p100-worth-it-2026/</guid>
    <pubDate>Sun, 27 Sep 2026 00:00:00 GMT</pubDate>
    <description>Around $89 for 16 GB of HBM2. It's the cheapest VRAM you can buy, as long as you can live with the catches.</description>
  </item>
  <item>
    <title>Q4_0 vs Q5 on a 27B: prompt speed is basically a wash</title>
    <link>https://lowbudgetlab.com/posts/q4-vs-q5-prompt-speed/</link>
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    <pubDate>Sun, 27 Sep 2026 00:00:00 GMT</pubDate>
    <description>I assumed the bigger quant was costing me prompt speed. Fifty production logs said otherwise.</description>
  </item>
  <item>
    <title>Splitting a 27B model across mismatched GPUs: tensor vs layer vs RPC</title>
    <link>https://lowbudgetlab.com/posts/splitting-27b-across-gpus/</link>
    <guid isPermaLink="true">https://lowbudgetlab.com/posts/splitting-27b-across-gpus/</guid>
    <pubDate>Thu, 24 Sep 2026 00:00:00 GMT</pubDate>
    <description>An RTX 3070 plus a Tesla P100 in one box beats adding more GPUs over the network. Here's why, with numbers.</description>
  </item>
  <item>
    <title>The one flag that made prompt processing 67% faster (and why I lost it)</title>
    <link>https://lowbudgetlab.com/posts/big-ubatch-prompt-speed/</link>
    <guid isPermaLink="true">https://lowbudgetlab.com/posts/big-ubatch-prompt-speed/</guid>
    <pubDate>Thu, 20 Aug 2026 00:00:00 GMT</pubDate>
    <description>Raising llama.cpp's ubatch took a 27B model from 171 to 286 tok/s on long prompts. Then it quietly disappeared from my launchers.</description>
  </item>
  <item>
    <title>Image-to-video on an 8 GB RTX 3070 with FramePack</title>
    <link>https://lowbudgetlab.com/posts/framepack-image-to-video-3070/</link>
    <guid isPermaLink="true">https://lowbudgetlab.com/posts/framepack-image-to-video-3070/</guid>
    <pubDate>Thu, 02 Jul 2026 00:00:00 GMT</pubDate>
    <description>A 4.5-second, on-model animation of a cartoon sprite on a green screen, in about 7 minutes on an 8 GB card.</description>
  </item>
  <item>
    <title>+65% decode on an 80B MoE from two cheap changes</title>
    <link>https://lowbudgetlab.com/posts/kv-cache-q4-moe-speedup/</link>
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    <pubDate>Wed, 13 May 2026 00:00:00 GMT</pubDate>
    <description>Quantizing the K cache to q4_0 and updating llama.cpp took an 80B MoE coder model from 12 to 20 tok/s.</description>
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