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Org card: stop clipping of the tagline and note
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index.html
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body { margin: 0; background: #0b0b0c; color: #e8e6e1; font-family: system-ui, -apple-system, Segoe UI, Roboto, sans-serif; line-height: 1.55; }
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main { max-width: 760px; margin: 0 auto; padding: 40px 16px; }
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h1 { color: #D4AF37; margin: 0 0 4px; font-size: 2rem; }
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h2 { color: #D4AF37; font-size: 1.15rem; margin-top: 28px; }
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a { color: #D4AF37; }
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img { width: 100%; height: auto; border-radius: 8px; margin: 16px 0; }
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<body>
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<main>
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<h1>Genrius AI</h1>
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<p class="
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<p><strong>Try it:</strong> <a href="https://huggingface.co/spaces/Genrius-AI/llm-vram-calculator" target="_blank" rel="noopener noreferrer">Will it fit your GPU? (calculator)</a> | <a href="https://github.com/Genrius-AI/pingala8-llm/releases/latest" target="_blank" rel="noopener noreferrer">One-click build, Windows and Linux, NVIDIA RTX 30/40/50</a></p>
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<table>
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<tr><th>Model</th><th>Size</th><th>WikiText-2 PPL, ours</th><th>IQ2_XXS, same size</th></tr>
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<tr><td><a href="https://huggingface.co/Genrius-AI/Qwen3-4B-Pingala8-2bit" target="_blank" rel="noopener noreferrer">Qwen3-4B-Pingala8-2bit</a></td><td>1.24 GB</td><td>16.64</td><td>28.61</td></tr>
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<tr><td><a href="https://huggingface.co/Genrius-AI/Llama-3.1-8B-Pingala8-2bit" target="_blank" rel="noopener noreferrer">Llama-3.1-8B-Pingala8-2bit</a></td><td>2.39 GB</td><td>9.14</td><td>12.35</td></tr>
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</table>
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<p class="
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<h2>Pingala-8: 2-bit LLMs for llama.cpp, no retraining</h2>
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<ul>
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<li>85% smaller: Qwen3-4B goes from 8.05 GB to 1.24 GB, and Llama 3.1 8B from 16.08 GB to 2.39 GB.</li>
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body { margin: 0; background: #0b0b0c; color: #e8e6e1; font-family: system-ui, -apple-system, Segoe UI, Roboto, sans-serif; line-height: 1.55; }
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main { max-width: 760px; margin: 0 auto; padding: 40px 16px; }
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h1 { color: #D4AF37; margin: 0 0 4px; font-size: 2rem; }
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.lead { color: #b9b4a8; margin: 0 0 28px; }
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h2 { color: #D4AF37; font-size: 1.15rem; margin-top: 28px; }
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a { color: #D4AF37; }
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img { width: 100%; height: auto; border-radius: 8px; margin: 16px 0; }
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<body>
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<main>
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<h1>Genrius AI</h1>
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<p class="lead">Generating Real Intelligence. We build AI models and make them small and fast enough to run on hardware people already own.</p>
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<p><strong>Try it:</strong> <a href="https://huggingface.co/spaces/Genrius-AI/llm-vram-calculator" target="_blank" rel="noopener noreferrer">Will it fit your GPU? (calculator)</a> | <a href="https://github.com/Genrius-AI/pingala8-llm/releases/latest" target="_blank" rel="noopener noreferrer">One-click build, Windows and Linux, NVIDIA RTX 30/40/50</a></p>
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<table>
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<tr><th>Model</th><th>Size</th><th>WikiText-2 PPL, ours</th><th>IQ2_XXS, same size</th></tr>
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<tr><td><a href="https://huggingface.co/Genrius-AI/Qwen3-4B-Pingala8-2bit" target="_blank" rel="noopener noreferrer">Qwen3-4B-Pingala8-2bit</a></td><td>1.24 GB</td><td>16.64</td><td>28.61</td></tr>
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<tr><td><a href="https://huggingface.co/Genrius-AI/Llama-3.1-8B-Pingala8-2bit" target="_blank" rel="noopener noreferrer">Llama-3.1-8B-Pingala8-2bit</a></td><td>2.39 GB</td><td>9.14</td><td>12.35</td></tr>
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</table>
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<p class="lead">Lower is better. The files need our patched llama.cpp build (NVIDIA CUDA); stock llama.cpp, Ollama and LM Studio cannot load them.</p>
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<h2>Pingala-8: 2-bit LLMs for llama.cpp, no retraining</h2>
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<ul>
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<li>85% smaller: Qwen3-4B goes from 8.05 GB to 1.24 GB, and Llama 3.1 8B from 16.08 GB to 2.39 GB.</li>
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