With 80 GB of VRAM, the A100 80GB runs Qwen2.5 14B Instruct at Q4_K_M entirely on the GPU with an 8K context (about 11.2 GB needed). At Q8_0 it fits entirely.
Q4_K_M · 8K context
The model needs about 11.2 GB and fits in the 77.6 GB available, with 66.4 GB to spare.
~11.2 GB (10.7 GB–11.8 GB) needed · estimate
Fits entirely in VRAM · 66.4 GB left
EstimateData updated 24 days agoSource: Run LLM Locally engine, Hugging Face config.json + model card
What makes this estimate less reliable
| Qwen2.5 14B Instruct Q8_08K~17.8 GB · 72–104 tok/s estimate | Excellent |
|---|---|
| Qwen2.5 14B Instruct Q6_K8K~14.3 GB · 87–129 tok/s estimate | Excellent |
| Qwen2.5 14B Instruct Q5_K_M8K~12.7 GB · 96–145 tok/s estimate | Excellent |
| Qwen2.5 14B Instruct Q4_K_M8K~11.2 GB · 106–164 tok/s estimate | Excellent |
| Qwen2.5 14B Instruct IQ4_XS8K~10.4 GB · 113–178 tok/s estimate | Excellent |
| Qwen2.5 14B Instruct Q3_K_M8K~9.6 GB · 120–192 tok/s estimate | Excellent |
Prices and links follow the market you choose.
NVIDIA
ExcellentRuns Qwen2.5 14B Instruct Q4_K_M entirely in memory
AMD
ExcellentRuns Qwen2.5 14B Instruct Q4_K_M entirely in memory
Apple Silicon
CompatibleRuns Qwen2.5 14B Instruct Q4_K_M entirely in memory
Unified memory PC
ExcellentRuns Qwen2.5 14B Instruct Q4_K_M entirely in memory
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