GPU Inference Benchmark
Exposes queryable GPU inference benchmark data (quantization, throughput, VRAM, concurrent users) as tools for LLM clients.
What is GPU Inference Benchmark?
GPU Inference Benchmark is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to exposes queryable gpu inference benchmark data (quantization, throughput, vram, concurrent users) as tools for llm clients.
Exposes queryable GPU inference benchmark data (quantization, throughput, VRAM, concurrent users) as tools for LLM clients.
This server falls under the Data Science & ML category on MCPgee, the world's largest MCP server directory with 33,000+ servers.
Features
- Exposes queryable GPU inference benchmark data (quantization
Use Cases
Maintainer
Works with
Installation
Manual Installation
npx ppbConfiguration
Configuration Details
claude_desktop_config.json
Performance
Response Metrics
Resource Usage
Frequently Asked Questions about GPU Inference Benchmark
What is GPU Inference Benchmark?
GPU Inference Benchmark is a Model Context Protocol (MCP) server that exposes queryable gpu inference benchmark data (quantization, throughput, vram, concurrent users) as tools for llm clients. It connects AI assistants to external tools and data sources through a standardized interface.
How do I install GPU Inference Benchmark?
Follow the installation instructions on the GPU Inference Benchmark GitHub repository. Clone the repo, install dependencies, and add the server config to your AI client.
Which AI clients work with GPU Inference Benchmark?
GPU Inference Benchmark works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.
Is GPU Inference Benchmark free to use?
Yes, GPU Inference Benchmark is open source and available under the MIT license. You can use it freely in both personal and commercial projects.
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Set Up GPU Inference Benchmark in Your Editor
Choose your AI client for step-by-step setup instructions.
Quick Config Preview
Add this to your claude_desktop_config.json or .cursor/mcp.json
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