NVIDIA Jetson AGX Orin 64GB — Benchmarks & Specs
Short answer: the NVIDIA Jetson AGX Orin 64GB generates a median 28.0 tokens/sec on 7-9B dense models at 4-bit (Q4) under llama.cpp, across 3 cited runs from MultimodalFlow and DFRobot. At the $3,379.00 Amazon price checked under an hour ago (prices change), that is 8.29 tok/s per $1,000, the SpecPicks Value Index.
- Median speed 28.0 tok/s 3 cited runs, 7-9B at Q4, llama.cpp
- Lowest linked price $3,379.00 Amazon, checked ; prices change
- Value Index 8.29 tok/s per $1,000 median speed ÷ the price above
Bottom line: how fast is the NVIDIA Jetson AGX Orin 64GB?
SpecPicks median: 28.0 tokens/sec across 3 cited single-user runs of 7-9B dense models at 4-bit (Q4) under llama.cpp (range 1.5–31.0 tok/s), from MultimodalFlow (2 runs), DFRobot. At the $3,379.00 Amazon price of the cheapest linked listing (checked ; prices change), that is a SpecPicks Value Index of 8.29 tok/s per $1,000. For local LLM inference it generates 27.0 tokens/sec running qwen3:30b-a3b (a mixture-of-experts model with ~3B active parameters, so dense models of similar size run far slower) at q4_K_M under llama.cpp, per Hackster.io. In MLPerf v3.1 ResNet-50 Image Classification Offline it scores 6,423.63 samples/s, per NVIDIA Developer. It has 64 GB of memory shared by the CPU and GPU, and the qwen3:30b-a3b run above (30B parameters) is the largest model on file at 4-bit quantization on it. Larger models have no sourced run on file.
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; the memory size is the on-paper spec; the SpecPicks median is computed here from the runs it names, each a row in the AI table, and the per-$1,000 figure divides it by the dated listing price. SpecPicks aggregates published measurements; it does not report first-party benchmark runs.
Amazon listing: $3,379.00
This Amazon listing is above the NVIDIA Jetson AGX Orin 64GB's $1,999 launch MSRP. Compare new and used listings on eBay before buying.
*Price sourced from Amazon.com. Last updated 2026-10-22. Price and availability subject to change.
The NVIDIA Jetson AGX Orin 64GB is an APU from the Jetson Orin family released in 2022 from NVIDIA. Key on-paper specs include 12 CPU cores, 2048 GPU cores, 64 GB of memory shared by the CPU and GPU, 204.8 GB/s of memory bandwidth. It launched with a $1,999 MSRP, though street prices typically diverge meaningfully from launch pricing — see the linked product cards below for current listings. Data on this page draws on 6 linked listings, 7 synthetic benchmark results, 28 community AI inference reports (top 14 shown), compiled from MultimodalFlow, NVIDIA Developer, Hackster.io, lowtouch.ai, NVIDIA Developer Forums, DFRobot, IoT Digital Twin PLM, jetson-containers, ProventusNova Blog; each table row links to its source. Read this page when shopping the NVIDIA Jetson AGX Orin 64GB, comparing it against other APUs in your build, or sizing it for a specific workload (synthetic benchmark scores or local LLM inference).
AI Inference Performance
Tokens per second under each model + quantization. Higher = faster generation. Bars compare runs across the same model.
| Model | Quantization | Relative | Tokens/sec | VRAM used | Source |
|---|---|---|---|---|---|
| llama3.1:8b | q4_K_M llama.cpp | 52.0 tok/s | — | ProventusNova Blog 2026-06-10 | |
| phi3:mini | q4_K_M llama.cpp | 47.0 tok/s | 2.8 GB | MultimodalFlow Blog 2026-05 | |
| phi3:3.8b | q4_K_M llama.cpp | 47.0 tok/s | 2.8 GB | MultimodalFlow 2026-05-29 | |
| llama3:8b | — mlc | 40.0 tok/s | — | DFRobot 2024-07 | |
| gemma3:4b | — ollama | 34.0 tok/s | — | NVIDIA Developer Forums 2026-02-17 | |
| qwen2.5:7b | q4_K_M llama.cpp | 31.0 tok/s | 5.2 GB | MultimodalFlow Blog 2026-05 | |
| llama3.1:8b | q4_K_M llama.cpp | 28.0 tok/s | 5.8 GB | MultimodalFlow Blog 2026-05 | |
| qwen3:30b-a3b | q4_K_M llama.cpp | 27.0 tok/s | — | Hackster.io 2025-07 | |
| llama2:7b | q4_0 llama.cpp | 1.5 tok/s | — | DFRobot Blog 2023-12-20 |
Batched serving throughput
| Model | Quantization | Relative | Tokens/sec (aggregate) | VRAM used | Source |
|---|---|---|---|---|---|
| qwen2.5-vl:3b | — tensorrt-llm batched | 225.7 tok/s aggregate | — | NVIDIA Developer Forums 2025-03 | |
| deepseek-r1-distill-qwen:7b | — vllm 8 concurrent requests | 180.4 tok/s aggregate | — | NVIDIA Developer Forums 2025-02 | |
| gemma2:2b | FP16 TensorRT-LLM batched | 120.0 tok/s aggregate | — | IoT Digital Twin PLM 2026-04-24 | |
| llama3.2:3b | INT4 TensorRT-LLM batched | 85.0 tok/s aggregate | — | IoT Digital Twin PLM 2026-04-24 | |
| llama2:7b | q4f16_ft mlc batched | 46.9 tok/s aggregate | — | jetson-containers (NVIDIA/dusty-nv) 2024-04 |
Synthetic Benchmarks
Higher is better. Bars are scaled within each benchmark family (multi-thread, single-thread, etc.) so you can compare like-with-like at a glance.
| Benchmark | Relative | Score | Source |
|---|---|---|---|
| MLPerf v3.1 ResNet-50 Image Classification Offline | 6,423.63 samples/s | NVIDIA Developer 2023-11 | |
| MLPerf v3.1 RNN-T Speech-to-Text Offline | 1,169.98 samples/s | NVIDIA Developer 2023-11 | |
| MLPerf v3.1 BERT-Large NLP Offline | 553.69 samples/s | NVIDIA Developer 2023-11 | |
| MLPerf Inference v4.0 Edge - YOLOv8n | 383 FPS | lowtouch.ai 2025-02-27 | |
| YOLOv8l (TensorRT, 60W) | 95 FPS | lowtouch.ai 2025-02-27 | |
| GPT-J 6B (MLPerf) | 0.15 samples/sec | lowtouch.ai 2025-02-27 | |
| MLPerf v4.0 GPT-J 6B Summarization Offline | 0.15 samples/s | NVIDIA Developer 2024-10 |
Products Featuring the NVIDIA Jetson AGX Orin 64GB
Full Specifications
| Memory | 64 GB |
|---|---|
| AI TOPS | 275 |
| CPU cores | 12 |
| GPU cores | 2048 |
| Memory bandwidth | 204.8 GB/s |
NVIDIA Jetson AGX Orin 64GB — Frequently Asked Questions
What is the NVIDIA Jetson AGX Orin 64GB best used for?
When was the NVIDIA Jetson AGX Orin 64GB released, and what was its launch MSRP?
Where do the NVIDIA Jetson AGX Orin 64GB benchmark numbers come from?
How many cores does the NVIDIA Jetson AGX Orin 64GB have, and how does it benchmark?
Where can I buy the NVIDIA Jetson AGX Orin 64GB?
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This page is the raw performance data. The guides below turn it into a ranked pick for a specific build.
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