VRAM Calculator
Check if your hardware can run specific AI models
Will Your GPU Actually Run This? 🤔
The brutally honest VRAM calculator that tells you what you can actually run
Analyzing 10 AI models across 83 GPUs • No marketing BS, just math
Reality Check:VRAM requirements vary by quantization. A 70B model needs 140GB at FP16, but only ~35GB at 4-bit. We calculate real requirements based on model architecture, not marketing claims.
Your GPU
RAM vs VRAM - What's the difference?
VRAM (GPU memory) is what matters for AI model speed. Models loaded in VRAM run fast.
RAM (system memory) can be used for CPU inference or offloading, but is 10-50x slower.
Mac users: Apple Silicon uses unified memory - your RAM acts as VRAM.
Quantization Guide
FP32 (Full Precision)Q100%
VRAM: 200%Speed: 0.5x
FP16 (Half Precision)Q99%
VRAM: 100%Speed: 1x
BF16 (Brain Float)Q99%
VRAM: 100%Speed: 1x
INT8Q95%
VRAM: 50%Speed: 1.5x
INT4Q88%
VRAM: 25%Speed: 2x
GGUF Q8_0Q96%
VRAM: 50%Speed: 1.4x
GGUF Q6_KQ94%
VRAM: 38%Speed: 1.6x
GGUF Q5_K_MQ92%
VRAM: 33%Speed: 1.7x
GGUF Q4_K_MQ90%
VRAM: 28%Speed: 1.8x
Model data from unified AI models database
GPU specifications from hardware database