High-efficiency, hardware-tested GGUF releases of Qwen3.8-27B (27 Billion Parameters, Dense Architecture). All models in this repository have been physically converted, verified on hardware (AMD Instinct MI300X with ROCm / HIP), and benchmarked for prompt throughput, token generation velocity, and benchmark accuracy against baseline models. This repository provides three specialized model tiers: — zraldv1-ac (Accuracy-Priority Tier): 17.08 GiB (18.3 GB). Near-lossless retention (99.68% accuracy), matches or outperforms standard Q6K and Q80 quality while saving ~10 GB VRAM compared to Q80. — zraldv1-ba (Balanced Sweet-Spot): 14.46 GiB (15.5 GB). Optimal balance (99.12% accuracy), fits cleanly in 16GB VRAM GPUs (e.g. RTX 4080, RTX 4060 Ti 16GB, Apple Silicon 16GB/24GB), delivering +3.92% higher retention than standard Q4KM. — zraldv1-cs (Compressed Size Tier): 10.18 GiB (10.9 GB). Maximum compression (62.3% size reduction from Q80), maintaining the $ge 90%$ accuracy floor (90.72% retention) with 76.33 tok/s generation velocity (+19.7% faster ⚡)**. Runs on 12GB VRAM cards and lightweight systems. Hardware Throughput Benchmark setup: AMD Instinct MI300X (192GB HBM3 VRAM, gfx942),…
Модальности:
Генерация текста
Области применения:
Генерация кода Логика и рассуждение Диалог / чат
Задача: Генерация текста
Автор: Zrald
Теги: gguf, llama.cpp, qwen, qwen3_8, conversational, coding, reasoning, endpoints_compatible
Лайков: 3 | Загрузок: 115
Описание основано на материалах HuggingFace. Перевод выполнен автоматически.
