~/can-i-run/qwen-3-30b-a3b
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Can I run Qwen3 30B A3B?

Short answer: yes, on a H100 80GB (80GB) at FP16/BF16. Long answer below.

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The math, in one paragraph.

$ ./vrambudget --explain qwen-3-30b-a3b

Qwen3 30B A3B has 30.5B parameters (MoE: 3.3B active per forward pass, but all 30.5B must fit in memory). At FP16 that's 61 GB of raw weights. Quantization shrinks that, but you also need budget for the KV cache (definition), framework overhead, and safety headroom. The rule of thumb: real usable budget on a card is roughly its nameplate VRAM minus 25%. That's how the table below was computed.

What hardware actually fits.

$ grep "fits" gpus.json
FP16/BF16
61GB
13 GPUs fit
H100 80GB80GBM3 Max 9696GBRTX Pro 600096GBM4 Max 128128GB+ 9 more
Q8_0
32GB
21 GPUs fit
RTX A600048GBRTX 6000 Ada48GBL40S48GBRadeon Pro W790048GB+ 17 more
Q5_K_M
21GB
22 GPUs fit
RTX 509032GBRTX A600048GBRTX 6000 Ada48GBL40S48GB+ 18 more
Q4_K_M
17GB
27 GPUs fit
RTX 309024GBRTX 3090 Ti24GBRTX 409024GBRX 7900 XTX24GB+ 23 more
Q3_K_M
13GB
27 GPUs fit
RTX 309024GBRTX 3090 Ti24GBRTX 409024GBRX 7900 XTX24GB+ 23 more

Pick your path.

$ ls strategies/
Tightest budget

Smallest GPU that fits Qwen3 30B A3B at any quant: H100 80GB at FP16/BF16.

Reference quality (FP16)

Lossless inference needs 61 GB. Pick from 13 cards.

Best quality on a 24GB card

Q4_K_M fits comfortably (17 GB weights).

Tune the math yourself

Open the calculator pre-tuned for Qwen3 30B A3B: ↗ /calc?model=qwen-3-30b-a3b

See the full model page.

$ ./open
$ openQwen3 30B A3B30.5BAlibaba · ctx 256K$ rankBest GPU for Qwen3 30B A3Bsee the ranking →ranked by fit quality

Discussion.

$ gh discussion list

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