Technical Snapshot

The PNY GeForce RTX 4070 Ti SUPER OC 16GB is a gaming desktop graphics card built on the NVIDIA Ada Lovelace architecture (AD103 GPU). It delivers 8,448 CUDA cores, 16 GB GDDR6X memory, on a 256-bit bus, boost clock of 2,655 MHz. The card connects via PCIe 4.0 x16 and draws 285W TDP, requiring a 700W minimum power supply. Part of the PNY OC product line, this card targets 4K/8K gaming, AI/ML inference, and professional rendering.

Use Case
4K/8K gaming, AI/ML inference, real-time ray tracing, 3D rendering, content creation
Compatibility
Requires PCIe x16 slot, 700W PSU, adequate case clearance
Category
Desktop Graphics Card — GeForce RTX 4070 Ti SUPER (Ada Lovelace)
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PNY GPU
PNY OC

GeForce RTX 4070 Ti SUPER OC 16GB

Ada Lovelace · AD103 · 8,448 CUDA Cores · 16 GB GDDR6X · PCIe 4.0 x16

Total number of CUDA parallel processing cores. Higher count enables faster rendering, AI inference, and compute workloads.
CUDA Cores 8,448
Video memory capacity and type. More VRAM allows higher-resolution textures, larger AI models, and multi-monitor setups.
VRAM 16 GB GDDR6X
Maximum GPU frequency under load. Higher boost clocks improve frame rates and compute throughput.
Boost Clock 2,655 MHz
Total board power consumption. Ensure your PSU has adequate wattage for stable operation.
TDP 285W
MPNVCG4070TS16TFXPB1-O
EAN751492786391
CategoryGraphics Cards
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GPU Core & Memory

GPU Chip NVIDIA AD103
Architecture Ada Lovelace
CUDA Cores 8,448
Base Clock 2,340 MHz
Boost Clock 2,655 MHz
VRAM 16 GB GDDR6X
Memory Bus 256-bit
PCIe Interface PCIe 4.0 x16
TDP 285W
Recommended PSU 700W
Cooling Dual fan
Display Outputs 3x DP 1.4a, 1x HDMI 2.1

Full Specifications

Data sourced from PNY product specifications and NVIDIA reference data
GPU
GPU ChipNVIDIA AD103
ArchitectureAda Lovelace
CUDA Cores8,448
Base Clock2,340 MHz
Boost Clock2,655 MHz
GPU VendorNVIDIA
Memory
VRAM16 GB GDDR6X
Memory Bus256-bit
Interface & Power
PCIe InterfacePCIe 4.0 x16
TDP285W
Recommended PSU700W
Card Design
Slot Width2.5-slot
CoolingDual fan
Display Outputs3x DP 1.4a, 1x HDMI 2.1
Product
BrandPNY
Brand SeriesOC
GPU SeriesGeForce RTX 4070 Ti SUPER
SegmentGaming
MPNVCG4070TS16TFXPB1-O
EAN751492786391
Physical
Weight1.56 kg
Package Dimensions30.5054 x 11.938 x 5.9436 cm

Support & Downloads

NVIDIA GeForce Game Ready Driver (Latest)Windows 10/11 64-bit
NVIDIA Drivers →
PNY GeForce RTX 4070 Ti SUPER OC 16GB User ManualPDF · Installation guide and specifications
PNY Support →
← Back to GPU Catalog

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Frequently Asked Questions

What motherboards are compatible with the RTX 4070 Ti SUPER OC 16GB?

The PNY GeForce RTX 4070 Ti SUPER OC 16GB uses a PCIe 4.0 x16 interface and is compatible with any motherboard that has a PCIe x16 slot. This includes AMD AM5 and AM4 motherboards as well as Intel LGA 1851 and LGA 1700 boards. PCIe is backward-compatible, so older PCIe 3.0 slots will work at reduced bandwidth.

What power supply is recommended for the RTX 4070 Ti SUPER OC 16GB?

A minimum 700W power supply is recommended for the PNY GeForce RTX 4070 Ti SUPER OC 16GB. The card has a TDP of 285W, so adequate PSU headroom is critical for stable operation under peak load, especially when paired with a high-end CPU.

Will the RTX 4070 Ti SUPER OC 16GB fit in my case?

Based on package dimensions, the PNY GeForce RTX 4070 Ti SUPER OC 16GB requires clearance of approximately 30.5054 cm (305 mm). Verify your case's maximum GPU length specification before purchasing. Also ensure sufficient PCIe slot clearance and adequate airflow.

How much VRAM does the RTX 4070 Ti SUPER OC 16GB have?

The PNY GeForce RTX 4070 Ti SUPER OC 16GB features 16 GB GDDR6X on a 256-bit bus. This is suitable for 4K/8K gaming, large AI/ML models, and professional rendering workloads.

Can the RTX 4070 Ti SUPER OC 16GB be used for AI and machine learning?

Yes. The PNY GeForce RTX 4070 Ti SUPER OC 16GB is built on NVIDIA's Ada Lovelace architecture with 8,448 CUDA cores and 16 GB VRAM, making it capable of AI inference and training workloads. It supports CUDA, Tensor Cores, and NVIDIA's AI frameworks. For dedicated enterprise AI, consider NVIDIA's professional-grade GPUs.

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