NVIDIA Jetson Orin NX 8GB — Benchmarks & Specs
Bottom line: how fast is the NVIDIA Jetson Orin NX 8GB?
For local LLM inference it generates 7.5 tokens/sec running gemma4:12b at q4_K_M under llama.cpp, per NVIDIA Developer Forums. Its 8 GB of memory, shared by the CPU and GPU, is the binding constraint for local inference: the gemma4:12b run above (12B parameters) is the largest model on file at 4-bit quantization on it.
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. SpecPicks aggregates published measurements; it does not report first-party benchmark runs.
The NVIDIA Jetson Orin NX 8GB is an APU from the Jetson Orin family released in 2023 from NVIDIA. Key on-paper specs include 6 CPU cores, 512 GPU cores, 8 GB of memory shared by the CPU and GPU. It launched with a $399 MSRP, though street prices typically diverge meaningfully from launch pricing. Data on this page draws on 15 community AI inference reports (top 13 shown), compiled from NVIDIA Technical Blog, Advantech-Containers, NVIDIA Developer Forums; each table row links to its source. Read this page when shopping the NVIDIA Jetson Orin NX 8GB, comparing it against other APUs in your build, or sizing it for a specific workload (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 |
|---|---|---|---|---|---|
| smollm2:1.7b | INT4 mlc | 51.5 tok/s | — | NVIDIA Technical Blog 2025-01-16 | |
| phi3.5-mini:3.8b | INT4 mlc | 30.8 tok/s | — | NVIDIA Technical Blog 2025-01-16 | |
| gemma2:2b | INT4 mlc | 26.6 tok/s | — | NVIDIA Technical Blog 2025-01-16 | |
| llama3.2:1b | Q8_0 llama.cpp | 18.5 tok/s | 1.3 GB | Advantech-Containers (GitHub) 2025-05-01 | |
| qwen2.5:7b | INT4 mlc | 17.1 tok/s | — | NVIDIA Technical Blog 2025-01-16 | |
| llama3.2:1b | q4_K_M llama.cpp | 16.5 tok/s | 1.0 GB | Advantech-Containers (GitHub) 2025-05-01 | |
| qwen2.5:1.5b | q4_K_M llama.cpp | 16.0 tok/s | 1.0 GB | Advantech-Containers (GitHub) 2025-05-01 | |
| llama3.1:8b | INT4 mlc | 15.9 tok/s | — | NVIDIA Technical Blog 2025-01-16 | |
| gemma4:4b | q4_K_M llama.cpp | 13.0 tok/s | — | NVIDIA Developer Forums 2026-06-06 | |
| gemma2:2b | q4_0 llama.cpp | 11.0 tok/s | 1.6 GB | Advantech-Containers (GitHub) 2025-05-01 | |
| llama3.2:3b | q4_K_M llama.cpp | 11.0 tok/s | 2.0 GB | Advantech-Containers (GitHub) 2025-05-01 | |
| gemma4:12b | q4_K_M llama.cpp | 7.5 tok/s | — | NVIDIA Developer Forums 2026-06-06 |
Batched serving throughput
| Model | Quantization | Relative | Tokens/sec (aggregate) | VRAM used | Source |
|---|---|---|---|---|---|
| llama3.2:3b | INT4 mlc batched | 34.5 tok/s aggregate | — | NVIDIA Technical Blog 2025-01-16 |
Full Specifications
| Memory | 8 GB |
|---|---|
| AI TOPS | 70 |
| CPU cores | 6 |
| GPU cores | 512 |
NVIDIA Jetson Orin NX 8GB — Frequently Asked Questions
What is the NVIDIA Jetson Orin NX 8GB best used for?
When was the NVIDIA Jetson Orin NX 8GB released, and what was its launch MSRP?
Where do the NVIDIA Jetson Orin NX 8GB benchmark numbers come from?
How many cores does the NVIDIA Jetson Orin NX 8GB have, and how does it benchmark?
Where can I buy the NVIDIA Jetson Orin NX 8GB?
Buying guides that rank the NVIDIA Jetson Orin NX 8GB's class
This page is the raw performance data. The guides below turn it into a ranked pick for a specific build.
Editorial guides covering the NVIDIA Jetson Orin NX 8GB
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