How much VRAM does Qwen 2.5 32B need at Q4_K_M? Single 24GB GPU sweet spot
Qwen 2.5 32B at Q4_K_M with native 128K context needs about 57.5 GB of VRAM, making it a fit for pooled cards or unified memory workstations.
Calculator
Estimated VRAM required
57.5 GB
32B params at Q4_K_M, 131,072 token context, batch 1, inference.
Estimate accuracy: Weights within ~2%. KV cache within ~5% for standard GQA models, ~10% for MLA (DeepSeek). Real VRAM may vary with framework (vLLM vs llama.cpp vs Transformers), Flash Attention, and driver overhead.
KV cache exceeds model weights: Consider lowering the context length to save on VRAM. Contexts between 8K and 64K are generally more typical for local setups.
Hardware that fits
How this is calculated
32B at Q4_K_M is roughly 17.9 GB of weights, 34.4 GB of KV cache, and 5.2 GB of activation overhead, totaling 57.5 GB.
Verdict
Qwen 2.5 32B Q4_K_M at reduced context is a sweet spot for 24 GB cards, but at its full native 128K context, the KV cache grows to 34.4 GB, pushing the total to 57.5 GB and requiring pooled cards or unified workstations.
More Qwen scenarios
Frequently asked questions
Can I run Qwen 2.5 32B on an RTX 3090?
Is Qwen 2.5 32B better than Llama 3.1 8B?
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