LLM Memory Usage Estimator

Calculate VRAM requirements for LLM inference

Model Weights
0GB
Loaded once
KV Cache
0GB
Per batch
Activations
0GB
During inference
Total VRAM
0GB
Recommended
📊 Memory Breakdown
Model Weights
0GB
Model parameters loaded into VRAM
KV Cache (Key-Value Cache)
0GB
Stores attention history for all sequences in batch
Activation Memory
0GB
Intermediate activations during forward pass
Total (with Overhead)
0GB
Recommended GPU VRAM capacity
Memory Distribution
Weights
70%
KV Cache
20%
Activations
10%
🖥️ GPU Recommendations
💡 Optimization Tips

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