metadata
license: mit
base_model: Qwen/Qwen3.5-9B
tags:
- hipfire
- amd
- rdna
- quantized
- qwen3.5
library_name: hipfire
Qwen3.5-9B for hipfire
Pre-quantized Qwen3.5-9B (DeltaNet hybrid) for hipfire, a Rust-native LLM inference engine for AMD RDNA GPUs.
Quantized from Qwen/Qwen3.5-9B.
Files
| File | Quant | Size | Min VRAM | Speed (5700 XT) |
|---|---|---|---|---|
| qwen3.5-9b.q4.hfq | HFQ4 | 4.5GB | 6GB | 45 tok/s |
| qwen3.5-9b.hfq6.hfq | HFQ6 | 6.8GB | 8GB | 37 tok/s |
Usage
# Install hipfire
curl -L https://raw.githubusercontent.com/Kaden-Schutt/hipfire/master/scripts/install.sh | bash
# Pull and run
hipfire pull qwen3.5:9b
hipfire run qwen3.5:9b "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.