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GPU Comparison
NVIDIA RTX 4000 SFF Ada Generation vs NVIDIA Jetson Orin NX 8 GB
NVIDIA RTX 4000 SFF Ada Generation vs NVIDIA Jetson Orin NX 8 GB
VS
NVIDIA RTX 4000 SFF Ada Generation
NVIDIA Jetson Orin NX 8 GB
We compared two Professional market GPUs: 20GB VRAM RTX 4000 SFF Ada Generation and 8GB VRAM Jetson Orin NX 8 GB to see which GPU has better performance in key specifications, benchmark tests, power consumption, etc.
Main Differences
NVIDIA RTX 4000 SFF Ada Generation 's Advantages
Boost Clock1560MHz
More VRAM (20GB vs 8GB)
Larger VRAM bandwidth (280.0GB/s vs 102.4GB/s)
5120 additional rendering cores
NVIDIA Jetson Orin NX 8 GB 's Advantages
Lower TDP (20W vs 70W)
Score
Benchmark
FP32 (float)
RTX 4000 SFF Ada Generation
+1123%
19.17 TFLOPS
Jetson Orin NX 8 GB
1.567 TFLOPS
RTX 4000 SFF Ada Generation
VS
Jetson Orin NX 8 GB
Graphics Card
Mar 2023
Release Date
Mar 2023
Quadro Ada
Generation
Tegra
Professional
Type
Professional
PCIe 4.0 x16
Bus Interface
PCIe 4.0 x4
Clock Speeds
720 MHz
Base Clock
-
1560 MHz
Boost Clock
-
1750 MHz
Memory Clock
1600 MHz
Memory
20GB
Memory Size
8GB
GDDR6
Memory Type
LPDDR5
160bit
Memory Bus
128bit
280.0GB/s
Bandwidth
102.4GB/s
Render Config
-
-
-
48
SM Count
8
6144
Shading Units
1024
192
TMUs
32
80
ROPs
16
192
Tensor Cores
32
48
RT Cores
-
128 KB (per SM)
L1 Cache
128 KB (per SM)
48 MB
L2 Cache
256 KB
-
-
-
Theoretical Performance
124.8 GPixel/s
Pixel Rate
12.24 GPixel/s
299.5 GTexel/s
Texture Rate
24.48 GTexel/s
19.17 TFLOPS
FP16 (half)
3.133 TFLOPS
19.17 TFLOPS
FP32 (float)
1.567 TFLOPS
299.5 GFLOPS
FP64 (double)
783.4 GFLOPS
Board Design
70W
TDP
20W
250 W
Suggested PSU
-
4x mini-DisplayPort 1.4a
Outputs
Portable Device Dependent
None
Power Connectors
-
Graphics Processor
AD104
GPU Name
GA10B
-
GPU Variant
TE980M-A1
Ada Lovelace
Architecture
Ampere
TSMC
Foundry
Samsung
5 nm
Process Size
8 nm
35.8 billion
Transistors
Unknown
294 mm²
Die Size
Unknown
Graphics Features
12 Ultimate (12_2)
DirectX
12 Ultimate (12_2)
4.6
OpenGL
4.6
3.0
OpenCL
3.0
1.3
Vulkan
1.3
8.9
CUDA
8.6
6.7
Shader Model
6.7
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