LM Studio Benchmark Documentation

Welcome to the LM Studio Benchmark documentation! This tool helps you measure and compare token/s performance across all your locally installed LLM models and their quantizations.

What is this?

A Python benchmark tool for LM Studio with a modern web dashboard that:

• Automatically tests all local LLM models and quantizations
• Measures token/s speeds with warmup and multiple runs
• Exports results in JSON, CSV, PDF, and interactive HTML formats
• Detects GPU capabilities (NVIDIA, AMD, Intel) and monitors VRAM usage
• Provides a web dashboard with live charts and filtering options
• Includes Linux tray controls with live status icons and quick actions

Quick Links

• Quickstart Guide — Get started in 5 minutes
• Configuration Reference — All CLI arguments and config file options
• Architecture Documentation — System architecture with Mermaid diagrams, including testing architecture
• REST API Integration — Advanced features with LM Studio API v1
• Hardware Monitoring — GPU, CPU, RAM tracking
• LLM Metadata Guide — Model capabilities and metadata
• User Data & Configuration — XDG directory structure and config management
• Agent Integration — How to integrate with LM Studio Agents

Features at a Glance

✅ Multi-model benchmarking with intelligent GPU offload ✅ Vision & tool-calling model detection ✅ Progressive VRAM management (automatic fallback) ✅ Caching system (skip already-tested models) ✅ Filter by quantization, architecture, params, context length ✅ Live web dashboard with 27 themes ✅ Linux tray controller with dynamic benchmark status icons ✅ REST API mode with parallel inference support ✅ Download progress tracking, MCP integration, stateful chats ✅ Response caching with 10,000x+ speedup for repeated prompts

Getting Started

Check out the Quickstart Guide to begin benchmarking your models!