Can I Run Qwen3 Coder 30B A3B Instruct on a AMD Instinct MI250X?
Runs at Q8_0 — near-lossless quality.
12 quantizations fit your 128GB
| Quant | Min VRAM | Recommended | File size | Headroom |
|---|---|---|---|---|
| Q8_0BEST | 33.4 GB | 34.9 GB | 32.5 GB | +94.6 GB |
| Q6_K | 26.1 GB | 27.6 GB | 25.1 GB | +101.9 GB |
| Q5_K_M | 22.7 GB | 24.2 GB | 21.7 GB | +105.3 GB |
| Q5_K_S | 22.1 GB | 23.6 GB | 21.1 GB | +106.0 GB |
| Q4_1 | 20.1 GB | 21.6 GB | 19.2 GB | +107.9 GB |
| Q4_K_M | 19.5 GB | 21.0 GB | 18.6 GB | +108.5 GB |
| Q4_K_S | 18.5 GB | 20.0 GB | 17.5 GB | +109.5 GB |
| Q4_0 | 18.2 GB | 19.7 GB | 17.4 GB | +109.8 GB |
| Q3_K_L | 14.6 GB | 16.1 GB | 14.6 GB | +113.4 GB |
| Q3_K_M | 13.8 GB | 15.3 GB | 14.7 GB | +114.2 GB |
| Q3_K_S | 12.7 GB | 14.2 GB | 13.3 GB | +115.3 GB |
| Q2_K | 11.0 GB | 12.5 GB | 11.3 GB | +117.0 GB |
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All quant variants, benchmark scores, and use-case tags.
Top-ranked open-source models that fit in 128GB.
FAQ
Can the AMD Instinct MI250X run Qwen3 Coder 30B A3B Instruct?
Yes. The AMD Instinct MI250X's 128GB of VRAM is enough to run Qwen3 Coder 30B A3B Instruct at Q8_0 quantization (33.4GB required).
What's the best quantization to use?
Q8_0 is the highest-precision quantization that fits in your 128GB. It uses about 33.4GB of memory and 34.9GB recommended for comfortable inference.
What if I need more headroom for context length?
KV cache memory grows with context length. The numbers above assume a baseline 2K-4K context. For long-context use (32K+), add another 2-6GB depending on the model architecture.