metadata
license: mit
base_model: Qwen/Qwen3-8B
tags:
- hipfire
- amd
- rdna
- quantized
- qwen3
library_name: hipfire
Qwen3-8B for hipfire
Pre-quantized Qwen3-8B (LLaMA (standard attention)) for hipfire, a Rust-native LLM inference engine for AMD RDNA GPUs.
Quantized from Qwen/Qwen3-8B.
Files
| File | Quant | Size | Min VRAM | Speed (5700 XT) |
|---|---|---|---|---|
| qwen3-8b.q4.hfq | HFQ4 | 4.1GB | 6GB | 59.9 tok/s |
| qwen3-8b-q4k-all.hfq | Q4_K | 4.3GB | 6GB | — |
Usage
# Install hipfire
curl -L https://raw.githubusercontent.com/Kaden-Schutt/hipfire/master/scripts/install.sh | bash
# Pull and run
hipfire pull qwen3:8b
hipfire run qwen3:8b "Hello"
Quantization Formats
- HFQ4: 4-bit, 256-weight groups (0.53 B/w). Best speed.
- HFQ6: 6-bit, 256-weight groups (0.78 B/w). Best quality. ~15% slower.
Both include embedded tokenizer and model config.
About hipfire
Rust + HIP inference engine for AMD consumer GPUs (RDNA1–RDNA4). No Python in the hot path. 9x faster than llama.cpp+ROCm on the same hardware.
- GitHub: Kaden-Schutt/hipfire
- All models: docs/MODELS.md
License
Model weights subject to original Qwen license. hipfire engine: MIT.