Spark Arena: LLM Performance Leaderboard on NVIDIA DGX Spark

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Spark Arena is a public leaderboard tracking Large Language Model performance on NVIDIA DGX Spark hardware. Powered by open-source tooling, it provides transparent benchmark comparisons across inference engines including vLLM, SGLang, TensorRT-LLM, and llama.cpp.

Key points

  1. Benchmarks executed on actual NVIDIA DGX Spark infrastructure using llama-benchy.
  2. Runtime engine comparisons across vLLM, SGLang, TensorRT-LLM, and llama.cpp.
  3. Full transparency with complete recipes, configuration files, and detailed metrics.
  4. Accompanied by open-source tooling such as spark-vllm-docker and sparkrun for managing inference workloads.
  5. A technical blog covers runbooks, reproducibility, and practical performance tuning.

Why it matters

Selecting the right inference runtime significantly impacts latency, throughput, and operational costs when deploying LLMs. Spark Arena provides hardware-backed benchmarks that help engineers make data-driven infrastructure choices.

Analysis

By pairing real hardware measurements with transparent configuration recipes and supporting tools like sparkrun and spark-vllm-docker, Spark Arena avoids black-box benchmarking and prioritises reproducibility across different runtime implementations.

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Summary generated by AI (Gemini 3.8 Flash, 27 September 2026). It may contain errors – the original source is authoritative.

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