can it run
Yes, but close to the edge. 32GB against a 24GB working set: it runs, with little room for long context windows or other processes.
weights 18.6GB + KV cache 0.38GB at 4k context vs ~32GB usable → full. 19.0 GB needed of 32 GB usable — headroom for context
computed roofline: 897 GB/s × 0.46–0.76 efficiency window / 1.9GB (Q4_K_M) — bands, never points.
MoE: file is 18.6GB (that decides fit) but only ~3B of experts activate per token (~1.9GB streamed) — band below is the active-expert estimate, optimistic; community MoE rows run several× the naive bandwidth math
| model file | 18.6GB (GGUF Q4_K_M) |
| minimum memory | 24GB working set |
| this machine | 32GB HBM2, 897 GB/s |
| params | 30B-A3B MoE |
| license | apache-2.0 |
| price | $645 |
easy run: ollama pull qwen3:30b-a3b
runs with: ollama · llama.cpp · koboldcpp · lm studio
→ Mac mini M5 Pro (64GB) — cheapest machine that runs it ($1669)
→ ASUS ExpertCenter Pro ET900N G3 (GB300) — this model on the biggest machine
→ every model the Tesla V100 32GB (used) can run — full list
→ RTX 3090 (24GB, used) — upgrade path machine