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No. Qwen3-Coder 30B-A3B (MoE) does not fit on RTX 3060 Ti 8GB: Q4_K_M needs 20.4 GB and 7.5 GB is usable.
Hardware: RTX 3060 Ti 8GB · Model: Qwen3-Coder 30B-A3B (MoE)
RTX 3060 Ti 8GB has 8 GB of VRAM and 448 GB/s of memory bandwidth. RTX 3070 8GB has the same memory and bandwidth, so the fit numbers match; this page is RTX 3060 Ti 8GB. The checker holds back 0.5 GB of VRAM for the driver and assumes 16 GB of system RAM, so fast memory usable by Ollama is 7.5 GB. Partial offload may also use 60% of that system RAM. Qwen3-Coder 30B-A3B (MoE) (30.5B, 3.3B active, Alibaba) at Q4_K_M is a 19 GB download and needs 20.4 GB with headroom for about 8k tokens.
| Best quant | Q4_K_M |
|---|---|
| Download size | 19 GB |
| Memory needed | 20.4 GB |
| Usable fast memory | 7.5 GB |
| Fit | does not fit |
| Estimated speed | no estimate, it does not fit |
| Command | ollama run qwen3-coder:30b |
Smallest hardware that runs it: RTX 3060 12GB at Q4_K_M (partial offload (slower), 20.4 GB needed, 11.5 GB usable, about 18 tok/s (estimate)). Can a RTX 3060 12GB run Qwen3-Coder 30B-A3B (MoE)?
A smaller Alibaba model that fits this hardware: Qwen 2.5 14B at Q4_K_M (partial offload (slower), 10.3 GB). Can a RTX 3060 Ti 8GB run Qwen 2.5 14B?
Open RTX 3060 Ti 8GB in the checkerEstimates, not benchmarks. Model sizes are ollama.com download sizes; memory needed adds headroom for ~8k tokens of context; speeds are rough figures from memory bandwidth. Data updated 2026-10-23.
A project by OnDevice Labs · llms.txt