About QuantizationCalculator.com

1. Our Mission

Running open-weights Large Language Models locally—whether on a single consumer RTX 4090, a dual-GPU workstation, or an Apple Silicon Mac Studio—often fails due to unexpected Out-Of-Memory (OOM) crashes when context windows expand. QuantizationCalculator.com was built to provide exact, architecture-aware memory telemetry before you download a 40GB+ checkpoint or purchase new hardware.

2. Why Our Mathematical Model Is Different

• Architecture-Specific KV Cache: Instead of applying a flat multiplier, we compute exact Key-Value tensor sizes from transformer layer count, GQA KV head count, head dimension, context token length, and KV cache quantization precision (FP16, Q8_0, Q4_0).
• Dense vs. Mixture-of-Experts (MoE) Decoupling: For MoE models like DeepSeek-R1 671B and Mixtral 8x22B, we use total parameters for VRAM capacity while using active parameters per token for memory-bandwidth speed estimation.
• Zero-Latency Edge Delivery: Served globally from 300+ Cloudflare Edge data centers in under 15 milliseconds with 100% WCAG 2.2 AAA screen-reader accessibility.