adiudiuu/tps

A static performance model for LLM inference: given (model, GPU, interconnect, workload), instantly answer VRAM feasibility, latency(TTFT, TPOT, ITL), and throughput.

Calculate token/s & GPU memory requirement for any LLM. Supports llama.cpp/ggml/bnb/QLoRA quantization

Feel how fast a local LLM runs before you buy the hardware

A CLI to estimate inference memory requirements for Hugging Face models, written in Python.

Local LLM Inference Speed Test Tool

A Lightweight LLM Inference Performance Simulator

Diagram-first LLM architecture, memory, hardware-fit, throughput, and verified cloud-cost explorer.

The htop for LLM inference see exactly where every GB of VRAM goes and get measured quantization savings.