NVIDIA Jetson Orin Nano Super 8GB vs NVIDIA A10G 24GB
Side-by-side specifications, performance, and rental pricing for datacenter AI workloads.
NVIDIA Jetson Orin Nano Super 8GB
Full specs →NVIDIA A10G 24GB
Full specs →Specifications
Performance (TFLOPS)
FLOPS by Precision
What actually differs
The Jetson Orin Nano Super is the newer part: Ampere, launched in 2024, against the A10G's Ampere from 2022. Newer architectures typically add lower-precision formats and better throughput per watt, so check the precision rows your workload actually uses.
Memory is 8 GB against 24 GB, fed at 102 GB/s versus 600 GB/s. More memory per GPU means larger models fit before you have to shard across cards, which often matters more than raw TFLOPS for inference.
For LLM training and inference, weight the FP8 and FP16 rows and memory capacity most heavily. For scientific and HPC workloads, the FP64 row is the one to read.
Frequently asked questions
Which has more memory, the Jetson Orin Nano Super or the A10G?
The A10G carries 24 GB of VRAM versus 8 GB for the Jetson Orin Nano Super. Memory bandwidth is 102 GB/s for the Jetson Orin Nano Super and 600 GB/s for the A10G.
How much power do the Jetson Orin Nano Super and the A10G draw?
The Jetson Orin Nano Super is rated at 25 W TDP and the A10G at 300 W. On FP32 throughput per watt, the A10G is the more efficient part.
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