bench
OfficialBenchmark API model latency and throughput.
AuthorOpenDCAI
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Quick benchmark of third-party API models for latency and throughput to help developers compare production-ready performance across endpoints.
Core Features & Use Cases
- Two Python scripts (test_models.py and test_anthropic.py) perform streaming-based benchmarks against different model endpoints.
- Automatically discover available models from /models and filter to the latest mainstream text models (Claude 4.x, GPT-5.x, Gemini-3.x, Qwen 3.x, GLM 4.7+, Kimi k2.5+), excluding outdated or irrelevant variants.
- Collect and compare metrics such as TTFB, total time, generated token count, and tokens-per-second to enable fast model selection.
- Supports multiple interface formats (OpenAI-like /v1/chat/completions and Anthropic /v1/messages) for cross-compatibility.
Quick Start
Use a concise instruction to start the benchmark by providing the API key and base URL for the endpoint.
Dependency Matrix
Required Modules
aiohttp
Components
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: bench Download link: https://github.com/OpenDCAI/leonai/archive/main.zip#bench Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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