by aquila | Jul 23, 2026 | Backends
🔗 SHA sum: 536edd46b9a93785bffc356c54b262b7 | Updated: 2026-07-20VerifyCPU: 8-core / 16-thread recommended for orchestration RAM: fast 5600MHz+ required to avoid memory bottlenecks Storage: extra room for future model updates and datasets GPU: RTX 4080 / RTX 4090...
by aquila | Jul 21, 2026 | Backends
📡 Hash Check: 9a772be25f5078e84397a22f2d8abb26 | 📅 Last Update: 2026-07-17VerifyProcessor: next-gen chip for heavy context processing RAM: fast 5600MHz+ required to avoid memory bottlenecks Storage: extra room for future model updates and datasets GPU: 16 GB+ video...
by aquila | Jul 20, 2026 | Backends
🔍 Hash-sum: 635504d56122455af0f2b057ac685fa2 | 🕓 Last update: 2026-07-15VerifyCPU: multi-threading optimized for fast prompt processing RAM: minimum 16 GB for stable 8B model loading Disk Space: 100 GB for multi-modal model vision components GPU: modern architecture...
by aquila | Jul 19, 2026 | Backends
🛡️ Checksum: 605a9e564ef215d2fda5f28e1ce2b1e6 — ⏰ Updated on: 2026-07-15VerifyProcessor: next-gen chip for heavy context processing RAM: at least 32 GB in dual-channel mode for bandwidth Disk: 150+ GB for high-context vector database storage Graphic Processor: RTX...
by aquila | Jul 18, 2026 | Backends
🗂 Hash: bbf1c70e8a190988f31963da518b0f54 • Last Updated: 2026-07-16VerifyProcessor: next-gen chip for heavy context processing RAM: fast 5600MHz+ required to avoid memory bottlenecks Disk Space:70 GB free space for full FP16 weights storage GPU: RTX 4080 / RTX 4090...
by aquila | Jul 17, 2026 | Backends
The most efficient approach for a local installation is leveraging Docker containers. Please follow the instructions listed below to get started. The loader auto-caches the model archive (several GBs included). Without any user input, the software calibrates...
