llamaperf

NVIDIA Jetson Orin Nano Super 8GB

NVIDIA · 8GB unified memory · 1 report

As of 12 Oct 2026, the models most run on the NVIDIA Jetson Orin Nano Super 8GB, with generation and prompt-processing medians from plain runs (one device, one request, no speculative decoding):

Engines people use on it: llama.cpp 1 (reports)

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Reported performance on the NVIDIA Jetson Orin Nano Super 8GB

These reports mix GPU counts and memory setups, so a model listed here may have needed extra cards or CPU offloading. The calculator estimates which models fit in 8 GB of unified memory.

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NVIDIA hardware
generation:
165.2 tokens/s
quant:
Q4_K_M (GGUF)

Reported by the source; GPU count, offloading and concurrent requests can change these figures. Prompt-processing speed is shown only when the source reports it; generation speed cannot tell us time to first token. Check the full setup before comparing.

User benchmarks SmolLM2-135M at 165.2 tok/s on a Jetson Orin Nano Super 8GB at 25W power mode. Setup is llama.cpp CUDA with Q4_K_M quant, 2048-token context, 256-token generation, single request, all layers on GPU. 25W beats 15W by 35-47% throughput and edges out MAXN on tokens per joule; llama.cpp is 1.37x faster than Ollama at 25W. The model uses 101 MB and draws about 5.6 W.

Oct 12, 2026

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Reported configurations

Individual observations from this page, not expected speeds or a ranking. Select a model to open its report, with the source and offloading conditions. Reported context may be a limit rather than actual input length.

Model / hardwareQuant / engineReported contextGeneration
SmolLM2 0.14B 0.1B
NVIDIA Jetson Orin Nano Super 8GB
Q4_K_M
llama.cpp
2,048165.2 tokens/s