SmolLM2 1.7B Instruct — VRAM Requirements
作者： Jakub Rusinowski · 最后更新： 2024年11月20日
How much GPU VRAM you need to run SmolLM2 SmolLM2 1.7B Instruct by HuggingFace locally, a 1.71B-parameter model. Figures are quantized weights + KV cache + framework overhead, computed from the model's parameter count and published architecture — not a throughput model. See /zh/methodology.
SmolLM2 1.7B Instruct needs about 3 GB VRAM at Q4_K_M.
VRAM by Quantization
| Quant | Bits/weight | Weights | Total VRAM |
|---|---|---|---|
| Q2_K | 2.63 | 0.6 GB | 3.0 GB |
| Q3_K_M | 3.41 | 0.7 GB | 3.1 GB |
| Q4_K_M | 4.83 | 1.0 GB | 3.4 GB |
| Q5_K_M | 5.67 | 1.2 GB | 3.6 GB |
| Q6_K | 6.56 | 1.4 GB | 3.8 GB |
| Q8_0 | 8.50 | 1.8 GB | 4.2 GB |
| F16 | 16.00 | 3.4 GB | 5.8 GB |
Switch quantization in the interactive calculator, or see the full SmolLM2 model page.
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Model creators: paste this into your Hugging Face model card README to link readers straight to this VRAM breakdown.
[](https://llmconfigurator.com/en/vram-calculator/smollm2-1.7b?utm_source=badge&utm_medium=referral&utm_campaign=readme_badge&utm_content=smollm2-1.7b)Estimates only — actual VRAM varies with context length, batch size, runtime and KV-cache settings.