EXAONE 3.5 7.8B — VRAM Requirements
作者： Jakub Rusinowski · 最后更新： 2026年7月21日
How much GPU VRAM you need to run EXAONE 3.5 EXAONE 3.5 7.8B by LG AI Research locally, a 7.8B-parameter model. Figures are quantized weights + KV cache + framework overhead from a memory-bandwidth roofline model.
EXAONE 3.5 7.8B needs about 6 GB VRAM at Q4_K_M.
VRAM by Quantization
| Quant | Bits/weight | Weights | Total VRAM |
|---|---|---|---|
| Q2_K | 2.63 | 2.6 GB | 3.4 GB |
| Q3_K_M | 3.41 | 3.3 GB | 4.1 GB |
| Q4_K_M | 4.83 | 4.7 GB | 5.5 GB |
| Q5_K_M | 5.67 | 5.5 GB | 6.3 GB |
| Q6_K | 6.56 | 6.4 GB | 7.2 GB |
| Q8_0 | 8.50 | 8.3 GB | 9.1 GB |
| F16 | 16.00 | 15.6 GB | 16.4 GB |
Switch quantization in the interactive calculator, or see the full EXAONE 3.5 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/exaone-3.5-7.8b)Estimates only — actual VRAM varies with context length, batch size, runtime and KV-cache settings.