💾 File hash: ac452e1666e6066b2da156b0bd80cdf0 (Update date: 2026-07-17) Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: 48 GB needed to prevent memory swapping to disk
🔐 Hash sum: acdf08532c6af4cddc82eebe26885257 | 📅 Last update: 2026-07-17 Verify Processor: high single-core performance needed for token latency RAM: fast 5600MHz+ required to avoid memory
🔧 Digest: 87e7230950308da4ccbe23713fd59dd2 • 🕒 Updated: 2026-07-13 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: 32 GB or higher for smooth 32k context lengths
🔧 Digest: 180ff85552a18f85bd1d6bfa43a52df1 • 🕒 Updated: 2026-07-13 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: 32 GB or higher for smooth 32k context lengths
🛠 Hash code: dcc23edf4b0bef0a92cf4edf291b1baa — Last modification: 2026-07-16 Verify Processor: 6-core 3.5 GHz minimum required RAM: required: 16 GB absolute minimum for small models Disk
The shortest path to running this model is by activating Hyper-V features. Follow the sequence of steps detailed below. The setup auto-streams the model assets
For an instant local deployment, running a pre-configured shell script is ideal. Follow the sequence of steps detailed below. The installer automatically pulls the model
For an instant local deployment, running a pre-configured shell script is ideal. Carefully read and apply the steps described below. The system automatically triggers a
