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1 change: 1 addition & 0 deletions README.md
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* **[genai-bench](https://github.com/sgl-project/genai-bench)**: Genai-bench is a powerful benchmark tool designed for comprehensive token-level performance evaluation of large language model (LLM) serving systems. ![Stars](https://img.shields.io/github/stars/sgl-project/genai-bench.svg?style=flat&color=green) ![Contributors](https://img.shields.io/github/contributors/sgl-project/genai-bench?color=green) ![LastCommit](https://img.shields.io/github/last-commit/sgl-project/genai-bench?color=green)
* **[Inference Benchmark](https://github.com/AI-Hypercomputer/inference-benchmark)**: A model server agnostic inference benchmarking tool that can be used to benchmark LLMs running on differet infrastructure like GPU and TPU. It can also be run on a GKE cluster as a container. ![Stars](https://img.shields.io/github/stars/AI-Hypercomputer/inference-benchmark.svg?style=flat&color=green) ![Contributors](https://img.shields.io/github/contributors/AI-Hypercomputer/inference-benchmark?color=green) ![LastCommit](https://img.shields.io/github/last-commit/AI-Hypercomputer/inference-benchmark?color=green)
* **[Inference Perf](https://github.com/kubernetes-sigs/inference-perf)**: GenAI inference performance benchmarking tool ![Stars](https://img.shields.io/github/stars/kubernetes-sigs/inference-perf.svg?style=flat&color=green) ![Contributors](https://img.shields.io/github/contributors/kubernetes-sigs/inference-perf?color=green) ![LastCommit](https://img.shields.io/github/last-commit/kubernetes-sigs/inference-perf?color=green)
* **[llm-speed](https://llm-speed.com)**: Crowdsourced, cryptographically signed benchmarks of LLM inference speed (decode tok/s, TTFT) across consumer GPUs, Apple Silicon, and hosted APIs. ![Stars](https://img.shields.io/github/stars/meadow-kun/llm-speed.svg?style=flat&color=green) ![Contributors](https://img.shields.io/github/contributors/meadow-kun/llm-speed?color=green) ![LastCommit](https://img.shields.io/github/last-commit/meadow-kun/llm-speed?color=green)


## Orchestration
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