Run MaziyarPanahi/Qwen3-14B-GGUF locally
MaziyarPanahi/Qwen3-14B-GGUF is a large language model with 14.77 billion parameters, built on the qwen3 architecture. It has been downloaded 277,182 times.
To run MaziyarPanahi/Qwen3-14B-GGUF locally at a 4,096-token context, its quantized versions need between 6.78 GB (Q2_K, lowest quality) and 28.94 GB (GGUF, highest quality) of memory, weights plus KV cache and a system margin included.
For most users the best balance is Q6_K, needing about 12.71 GB. That means MaziyarPanahi/Qwen3-14B-GGUF fits entirely in the VRAM of an 8 GB GPU or larger, running fully on the GPU.
All quantizations
| Quant. | Bits | Quality | Weights | KV | Total | Speed~ | Verdict |
|---|---|---|---|---|---|---|---|
| Q2_K | 3.12 | Low | 5.36 GB | 0.62 GB | 6.78 GB | 9.3 t/s | Offload |
| Q3_K_M | 3.97 | Fair | 6.82 GB | 0.62 GB | 8.24 GB | 7.3 t/s | Offload |
| Q3_K_L | 4.28 | Good | 7.36 GB | 0.62 GB | 8.78 GB | 6.8 t/s | Offload |
| Q4_K_M | 4.88 | Good | 8.38 GB | 0.62 GB | 9.81 GB | 6.0 t/s | Offload |
| Q5_K_M | 5.7 | Very good | 9.79 GB | 0.62 GB | 11.22 GB | 5.1 t/s | Offload |
| Q6_K | 6.57 | Excellent | 11.29 GB | 0.62 GB | 12.71 GB | 4.4 t/s | Offload |
| GGUF | 16.0 | Excellent | 27.51 GB | 0.62 GB | 28.94 GB | — | Insufficient |
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/Qwen3-14B-GGUF?
You need about 6.78 GB of VRAM to run MaziyarPanahi/Qwen3-14B-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/Qwen3-14B-GGUF on an 8 GB GPU?
Yes. With 8 GB of VRAM you can run MaziyarPanahi/Qwen3-14B-GGUF fully on the GPU using Q2_K (about 6.78 GB).
Can I run MaziyarPanahi/Qwen3-14B-GGUF on a 16 GB GPU?
Yes. With 16 GB of VRAM you can run MaziyarPanahi/Qwen3-14B-GGUF fully on the GPU using Q6_K (about 12.71 GB).
Can I run MaziyarPanahi/Qwen3-14B-GGUF on a 24 GB GPU?
Yes. With 24 GB of VRAM you can run MaziyarPanahi/Qwen3-14B-GGUF fully on the GPU using Q6_K (about 12.71 GB).
What is the best quantization for MaziyarPanahi/Qwen3-14B-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.