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NVIDIA Jetson AGX Orin 32GB
NVIDIA · APU · Jetson Orin

NVIDIA Jetson AGX Orin 32GB — Benchmarks & Specs

$999 MSRP2022

Bottom line: how fast is the NVIDIA Jetson AGX Orin 32GB?

For local LLM inference it generates 120.0 tokens/sec running gemma2:2b at FP16 under TensorRT-LLM, per IoT Digital Twin PLM.

Every figure above is a row in the tables below, and each row links out to the review or public benchmark database the number was taken from. SpecPicks aggregates published measurements; it does not report first-party benchmark runs.

The NVIDIA Jetson AGX Orin 32GB is an APU from the Jetson Orin family released in 2022 from NVIDIA. It launched with a $999 MSRP, though street prices typically diverge meaningfully from launch pricing — see the linked product cards below for current Amazon listings. Data on this page draws on 12 community AI inference reports, aggregated from public benchmark databases (TechPowerUp, PassMark, Geekbench, Cinebench) and the LocalLLaMA community. Read this page when shopping the NVIDIA Jetson AGX Orin 32GB, comparing it against other APUs in your build, or sizing it for a specific workload (gaming at 1080p/1440p/4K, productivity benchmarks, or local LLM inference).

AI Inference Performance

Tokens per second under each model + quantization. Higher = faster generation. Bars compare runs across the same model.

Local LLM inference throughput on the NVIDIA Jetson AGX Orin 32GB, in generated tokens per second. Higher is better; each row links to the community report or benchmark database it came from.
Model Quantization Relative Tokens/sec VRAM used Source
gemma2:2b FP16 TensorRT-LLM 120.0 tok/s IoT Digital Twin PLM 2026-04-01
gemma2:2b FP16 other 120.0 tok/s IoT Digital Twin PLM 2026-04-24
llama3.2:3b q4_0 other 85.0 tok/s 3.2 GB IoT Digital Twin PLM 2026-04-24
llama3.2:3b INT4 TensorRT-LLM 85.0 tok/s 3.2 GB IoT Digital Twin PLM 2026-04-01
phi3.5-mini:3.8b INT4 TensorRT-LLM 62.0 tok/s IoT Digital Twin PLM 2026-04-01
phi3.5-mini:3.8b q4_0 other 62.0 tok/s IoT Digital Twin PLM 2026-04-24
llama3.1:8b q4_K_M llama.cpp 52.0 tok/s ProventusNova 2026-06-10
phi3-mini:3.8b q4_K_M llama.cpp 47.0 tok/s 2.8 GB MultimodalFlow 2026-05-29
llama3:8b q4_0 other 40.0 tok/s DFRobot 2024-07-12
qwen3-vl:4b q4_K_M llama.cpp 32.7 tok/s 2.3 GB GitHub llama.cpp discussion #17732 2025-06-01
qwen2.5:7b q4_K_M llama.cpp 31.0 tok/s 5.2 GB MultimodalFlow 2026-05-29
llama3.1:8b q4_K_M llama.cpp 28.0 tok/s 5.8 GB MultimodalFlow 2026-05-29

Full Specifications

ram gb32
ai tops275
cpu cores12
gpu cores1792

NVIDIA Jetson AGX Orin 32GB — Frequently Asked Questions

What is the NVIDIA Jetson AGX Orin 32GB best used for?
NVIDIA Jetson AGX Orin 32GB is a Jetson Orin-family integrated CPU+GPU SoC. Use it for mainstream desktops and gaming-focused builds. Check the synthetic benchmark scores below for at-a-glance comparison.
When was the NVIDIA Jetson AGX Orin 32GB released, and what was its launch MSRP?
NVIDIA Jetson AGX Orin 32GB launched in 2022 at a $999 MSRP. Street prices diverge from launch pricing over a product's lifetime — check the linked Amazon listings on this page for current availability.
Where do the benchmark numbers on this page come from?
Synthetic benchmarks are scraped from public databases (TechPowerUp, PassMark, Geekbench Browser, Cinebench leaderboards). AI inference numbers come from the LocalLLaMA community (Reddit threads, llama.cpp / Ollama discussion logs, and Phoronix when available). Every benchmark row carries an inline source citation — click through to verify the original number.
How does the NVIDIA Jetson AGX Orin 32GB compare to its predecessor?
Compare NVIDIA Jetson AGX Orin 32GB side-by-side against other APUs on the Compare tool below. Synthetic benchmark scores let you place this SKU within its generation; the spec table shows the architectural and process-node differences from one generation to the next.
Where can I buy the NVIDIA Jetson AGX Orin 32GB?
Active Amazon listings aren't on file for this exact SKU yet. See the linked benchmark sources and the Compare tool for adjacent parts that may be in stock — and check the /benchmarks index for the latest curated picks in this category.

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