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Hardware · NVIDIA

What AI models can the NVIDIA Jetson Orin Nano Super (8 GB) run?

Unified memory
8.0 GB
Usable for models
6.0 GB
Memory bandwidth
102 GB/s
FP16 compute
2.1 TFLOPS
Released
2024

macOS lets the GPU use roughly two-thirds to three-quarters of unified memory by default, so we plan around that figure rather than the full 8.0 GB.

Specifications

MakerNVIDIA
TypeUnified-memory system on a chip
GPU share of memory75% (what the GPU can typically be given for a model)
ChipApple NVIDIA Jetson Orin Nano Super
Unified memory8.0 GB
Usable for AI models6.0 GB
Memory bandwidth102 GB/s
FP16 compute2.1 TFLOPS
InterfaceUNIFIED
Released2024

1 product with the NVIDIA Jetson Orin Nano Super (8 GB)

Best LLMs for the NVIDIA Jetson Orin Nano Super (8 GB)

Grade · points Model Quant Memory Speed Fit
79 ptsGreat (A) · 79 of 100 points: Model quality 26.1/45, Memory fit 25.0/25, Speed 12.9/15, Memory use 15.0/15 TMax 4BAi2 Q4_K_M 3.9 GB 29.7 tok/s Runs well
78 ptsGreat (A) · 78 of 100 points: Model quality 26.5/45, Memory fit 25.0/25, Speed 12.3/15, Memory use 15.0/15 Qwen3.5 4BAlibaba Q4_K_M 4.2 GB 26.9 tok/s Runs well
78 ptsGreat (A) · 78 of 100 points: Model quality 26.5/45, Memory fit 25.0/25, Speed 11.7/15, Memory use 15.0/15 Gemma 4 E2BGoogle Q4_K_M 4.3 GB 24.5 tok/s Runs well
78 ptsGreat (A) · 78 of 100 points: Model quality 25.7/45, Memory fit 25.0/25, Speed 12.5/15, Memory use 15.0/15 Agents-A1 4BInternScience Q4_K_M 4.1 GB 27.6 tok/s Runs well
77 ptsGreat (A) · 77 of 100 points: Model quality 24.8/45, Memory fit 25.0/25, Speed 12.5/15, Memory use 15.0/15 Fara 1.5 4BMicrosoft Q4_K_M 4.1 GB 27.6 tok/s Runs well
77 ptsGreat (A) · 77 of 100 points: Model quality 23.9/45, Memory fit 25.0/25, Speed 13.2/15, Memory use 15.0/15 Qwen3 4B Thinking 2507Alibaba Q4_K_M 4.7 GB 31.1 tok/s Runs well
77 ptsGreat (A) · 77 of 100 points: Model quality 28.0/45, Memory fit 24.0/25, Speed 10.1/15, Memory use 15.0/15 TMax 9BAi2 Q3_K_M 5.7 GB 18.1 tok/s Tight fit
76 ptsGreat (A) · 76 of 100 points: Model quality 22.7/45, Memory fit 24.0/25, Speed 15.0/15, Memory use 15.0/15 Ling 3.0 Tiny (8B-A1.3B)Ant Group (inclusionAI) Q3_K_M 5.2 GB 62.3 tok/s Tight fit
76 ptsGreat (A) · 76 of 100 points: Model quality 23.1/45, Memory fit 25.0/25, Speed 13.2/15, Memory use 15.0/15 Qwen3 4B Instruct 2507Alibaba Q4_K_M 4.7 GB 31.1 tok/s Runs well
76 ptsGreat (A) · 76 of 100 points: Model quality 22.2/45, Memory fit 25.0/25, Speed 13.9/15, Memory use 15.0/15 Granite 4.2 3BIBM Q4_K_M 4.0 GB 34.2 tok/s Runs well
75 ptsGreat (A) · 75 of 100 points: Model quality 23.1/45, Memory fit 25.0/25, Speed 12.6/15, Memory use 15.0/15 Qwen3-VL 4B InstructAlibaba Q4_K_M 5.0 GB 28.2 tok/s Runs well
75 ptsGreat (A) · 75 of 100 points: Model quality 25.7/45, Memory fit 24.0/25, Speed 10.7/15, Memory use 15.0/15 Gemma 4 E4BGoogle Q3_K_M 5.1 GB 20.2 tok/s Tight fit

Best Image models for the NVIDIA Jetson Orin Nano Super (8 GB)

Grade · points Model Precision Memory Time per output Fit
78 ptsGreat (A) · 78 of 100 points: Model quality 32.6/45, Memory fit 20.0/25, Speed 10.7/15, Memory use 15.0/15 FLUX.2 [klein] 4BBlack Forest Labs Q4 GGUF 4.6 GB 20 s Runs well
76 ptsGreat (A) · 76 of 100 points: Model quality 23.8/45, Memory fit 23.0/25, Speed 15.0/15, Memory use 15.0/15 SDXL-Lightning (4-step)ByteDance FP8 5.6 GB 9.9 s Tight fit
74 ptsGreat (A) · 74 of 100 points: Model quality 25.6/45, Memory fit 23.0/25, Speed 11.1/15, Memory use 15.0/15 DreamShaper XL v2 TurboLykon FP8 5.6 GB 18 s Tight fit
72 ptsGreat (A) · 72 of 100 points: Model quality 17.6/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 15.0/15 SDXL TurboStability AI FP8 4.2 GB 2.1 s Runs well
71 ptsGood (B) · 71 of 100 points: Model quality 27.3/45, Memory fit 23.0/25, Speed 5.9/15, Memory use 15.0/15 Juggernaut XL v9RunDiffusion FP8 5.6 GB 64 s Tight fit
71 ptsGood (B) · 71 of 100 points: Model quality 27.3/45, Memory fit 23.0/25, Speed 5.9/15, Memory use 15.0/15 RealVisXL V5.0SG161222 FP8 5.6 GB 64 s Tight fit

Best Video models for the NVIDIA Jetson Orin Nano Super (8 GB)

Grade · points Model Precision Memory Time per output Fit
67 ptsGood (B) · 67 of 100 points: Model quality 15.8/45, Memory fit 25.0/25, Speed 11.4/15, Memory use 15.0/15 AnimateDiff v3 (SD 1.5)Shanghai AI Lab FP16 4.7 GB 5.2 min Runs well
58 ptsGood (B) · 58 of 100 points: Model quality 22.1/45, Memory fit 12.0/25, Speed 9.4/15, Memory use 15.0/15 LTX-Video 2BLightricks FP8 4.0 GB 7.7 min Runs well
52 ptsUsable (C) · 52 of 100 points: Model quality 19.8/45, Memory fit 12.0/25, Speed 6.1/15, Memory use 15.0/15 CogVideoX 2BZhipu AI FP8 4.7 GB 18.4 min Runs well

Best LLMs by task on this hardware Open in Model Finder

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.