# Nvidia reports edge-agent benchmark result on Jetson AGX Thor

_Published Wednesday, September 16, 2026 at 8:07 PM EDT · AI · Latest · Tier 2 — Notable_

![Nvidia reports edge-agent benchmark result on Jetson AGX Thor — Primary](https://developer-blogs.nvidia.com/wp-content/uploads/2026/09/image5-6.webp)

Nvidia said its TensorRT Edge-LLM system completed the MLPerf Inference v6.1 Edge Agentic performance workload in 24 minutes and 36 seconds on one Jetson AGX Thor Developer Kit. The company reported 52.33 tokens per second running Qwen3.6-27B, compared with two hours and 37 minutes for the cited llama.cpp reference submission. Nvidia attributed the result to NVFP4 quantization, tree-based multi-token prediction and reuse of cached conversation state. The workload contained 20 software-engineering agent conversations and 1,007 generated turns.

## Sources

- [NVIDIA Technical Blog](https://developer.nvidia.com/blog/tensorrt-edge-llm-completes-the-mlperf-edge-agentic-benchmark-6-4x-faster-on-jetson-agx-thor/)

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Canonical: https://techandbusiness.org/newswire/JVMTDOpi2hpPk8xji2ZtyT
Published: 2026-09-17T00:07:05.792Z
Story chronology: 2026-09-16T20:37:07.000Z
Retrieved: 2026-09-17T01:51:08.594Z
Publisher: Tech & Business (techandbusiness.org)