Zrald-AI Qwen 3.8 27B (zraldv1-ba - Balanced Sweet-Spot Tier)
Official high-efficiency GGUF release of Qwen3.8-27B optimized for Balanced Sweet-Spot Tier.
This repository contains zraldv1-ba.gguf (14.46 GiB / 15.52 GB), physically benchmarked on AMD Instinct MI300X hardware.
For cross-comparison tables against standard Q8_0, Q6_K, Q5_K, Q4_K, and Q2_K models, visit the master repository:
Zrald/Zrald-AI-model-quant-qwen-3.8-27b
Key Performance Indicators
- Physical File Size: 14.46 GiB (15.52 GB)
- Accuracy Retention: 99.12%
- Prompt Processing Throughput: 1,103.4 tok/s
- Token Generation Velocity: 64.7 tok/s
- Recommended Minimum VRAM: 16 GB
- Profile: Optimal balance of size and intelligence (99.12% retention). Fits 16GB consumer GPUs and beats standard Q4_K_M by +3.92% accuracy.
Quickstart with llama.cpp
1. Download Model File
huggingface-cli download Zrald/Zrald-AI-qwen-3.8-27b-zraldv1-ba zraldv1-ba.gguf --local-dir ./models
2. Run Single Prompt
./build/bin/llama-cli \
-m ./models/zraldv1-ba.gguf \
-ngl 99 \
-c 4096 \
-p "<|im_start|>user\nSolve 15 * 14 step-by-step.<|im_end|>\n<|im_start|>assistant\n" \
-n 128 \
--single-turn
3. Run Interactive Chat
./build/bin/llama-cli \
-m ./models/zraldv1-ba.gguf \
-ngl 99 \
-c 8192 \
-cnv
4. Launch OpenAI-Compatible API Server
./build/bin/llama-server \
-m ./models/zraldv1-ba.gguf \
-ngl 99 \
-c 16384 \
--host 0.0.0.0 \
--port 8080
Citation & Acknowledgments
- Base model by the Qwen Team (Alibaba) under Apache 2.0.
- Runtime by Georgi Gerganov and the llama.cpp community.