---
base_model: Qwen/Qwen3-Coder-30B-A3B
tags:
- awq
- 4-bit
- rdna4
- gfx1201
- rocm
- sglang
- quantized
license: apache-2.0
---

# Qwen3-Coder-30B MoE AWQ 4-bit

AWQ 4-bit quantization of [Qwen3 Coder 30B-A3B](https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B) optimized for AMD RDNA4 (gfx1201) inference with [SGLang](https://github.com/sgl-project/sglang).

## Model Details

| | |
|---|---|
| **Base model** | [Qwen/Qwen3-Coder-30B-A3B](https://huggingface.co/Qwen/Qwen3-Coder-30B-A3B) |
| **Architecture** | MoE (128 experts, top-8) |
| **Parameters** | 30B total / 3B active |
| **Layers** | 48 |
| **Context** | 32K (tested), 262K (max) |
| **Quantization** | AWQ 4-bit, group_size=128 |

## Performance (2x AMD Radeon AI PRO R9700, TP=2)

- **Decode speed**: 30 tok/s single-user on 2x R9700
- **Launch**: `scripts/launch.sh coder-30b`

## Notes

Best throughput MoE model for coding tasks. 166 tok/s at 32 concurrent users.

## Usage with SGLang

```bash
git clone https://github.com/mattbucci/2x-R9700-RDNA4-GFX1201-sglang-inference
cd 2x-R9700-RDNA4-GFX1201-sglang-inference
./scripts/setup.sh
scripts/launch.sh coder-30b
```

See the [RDNA4 Inference Repository](https://github.com/mattbucci/2x-R9700-RDNA4-GFX1201-sglang-inference) for full setup instructions, patches, and benchmarks.

## Hardware

Tested on 2x AMD Radeon AI PRO R9700 (gfx1201, RDNA4, 32+34 GB VRAM) with ROCm 7.2 and SGLang v0.5.10 + RDNA4 patches.