Run MaziyarPanahi/Qwen3-30B-A3B-GGUF locally
MaziyarPanahi/Qwen3-30B-A3B-GGUF is a very large language model with 30.53 billion parameters, built on the qwen3moe architecture. It has been downloaded 271,081 times.
To run MaziyarPanahi/Qwen3-30B-A3B-GGUF locally at a 4,096-token context, its quantized versions need between 11.47 GB (Q2_K, lowest quality) and 24.36 GB (Q6_K, highest quality) of memory, weights plus KV cache and a system margin included.
For most users the best balance is Q2_K, needing about 11.47 GB. That means MaziyarPanahi/Qwen3-30B-A3B-GGUF fits entirely in the VRAM of a 12 GB GPU or larger, running fully on the GPU.
All quantizations
| Quant. | Bits | Quality | Weights | KV | Total | Speed~ | Verdict |
|---|---|---|---|---|---|---|---|
| Q2_K | 2.95 | Low | 10.49 GB | 0.19 GB | 11.47 GB | 38.1 t/s | Fits in VRAM |
| Q3_K_M | 3.85 | Fair | 13.7 GB | 0.19 GB | 14.69 GB | 3.6 t/s | Offload |
| Q3_K_L | 4.17 | Fair | 14.81 GB | 0.19 GB | 15.8 GB | 3.4 t/s | Offload |
| Q4_K_M | 4.86 | Good | 17.28 GB | 0.19 GB | 18.27 GB | 2.9 t/s | Offload |
| Q5_K_M | 5.69 | Very good | 20.23 GB | 0.19 GB | 21.22 GB | 2.5 t/s | Offload |
| Q6_K | 6.57 | Excellent | 23.37 GB | 0.19 GB | 24.36 GB | 2.1 t/s | Offload |
KV cache computed from the model's exact architecture. Speed is a rough estimate bounded by memory bandwidth.
Frequently asked questions
How much VRAM do you need to run MaziyarPanahi/Qwen3-30B-A3B-GGUF?
You need about 11.47 GB of VRAM to run MaziyarPanahi/Qwen3-30B-A3B-GGUF entirely on the GPU using the Q2_K quantization (at a 4,096-token context). Smaller quantizations lower the requirement at the cost of quality.
Can I run MaziyarPanahi/Qwen3-30B-A3B-GGUF on an 8 GB GPU?
Partially. MaziyarPanahi/Qwen3-30B-A3B-GGUF only fits on an 8 GB GPU by offloading part of it to system RAM (with Q5_K_M), which runs but is slower.
Can I run MaziyarPanahi/Qwen3-30B-A3B-GGUF on a 16 GB GPU?
Yes. With 16 GB of VRAM you can run MaziyarPanahi/Qwen3-30B-A3B-GGUF fully on the GPU using Q3_K_L (about 15.8 GB).
Can I run MaziyarPanahi/Qwen3-30B-A3B-GGUF on a 24 GB GPU?
Yes. With 24 GB of VRAM you can run MaziyarPanahi/Qwen3-30B-A3B-GGUF fully on the GPU using Q5_K_M (about 21.22 GB).
What is the best quantization for MaziyarPanahi/Qwen3-30B-A3B-GGUF?
If memory allows, higher bits-per-weight means better quality. A common sweet spot is a Q4_K_M or Q5_K_M quantization, which keeps most of the quality while roughly halving the memory versus 8-bit. Pick the highest quantization that still fits in your VRAM.