Performance Rating
The GeForce RTX 4070 10 GB is a graphics card by NVIDIA, that was never released. Built on the 5 nm process, and based on the AD104 graphics processor, in its AD104-275-A1 variant, the card supports DirectX 12 Ultimate. This ensures that all modern games will run on GeForce RTX 4070 10 GB. Additionally, the DirectX 12 Ultimate capability guarantees support for hardware-raytracing, variable-rate shading and more, in upcoming video games. The AD104 graphics processor is an average sized chip with a die area of 294 mm² and 35,800 million transistors. Unlike the fully unlocked GeForce RTX 4070 Ti, which uses the same GPU but has all 7680 shaders enabled, NVIDIA has disabled some shading units on the GeForce RTX 4070 10 GB to reach the product's target shader count. It features 7168 shading units, 224 texture mapping units, and 80 ROPs. Also included are 224 tensor cores which help improve the speed of machine learning applications. The card also has 56 raytracing acceleration cores. NVIDIA has paired 10 GB GDDR6X memory with the GeForce RTX 4070 10 GB, which are connected using a 160-bit memory interface. The GPU is operating at a frequency of 2355 MHz, which can be boosted up to 2520 MHz, memory is running at 1313 MHz (21 Gbps effective).
Contents:
Memory ML Performance Compute Power Architecture & Compatibility ML Software Support Clocks & Performance Power Consumption Rendering AdditionalMemory
Memory Size
Memory Type
Memory Bandwidth
Memory Bus Width
ML Performance
FP16 (Half Precision)
BF16 (Brain Float)
TF32 (TensorFloat)
Compute Power
FP32 (Single Precision)
FP64 (Double Precision)
CUDA Cores
RT Cores
Architecture & Compatibility
GPU Architecture
SM (Streaming Multiprocessor)
PCIe Version
ML Software Support
CUDA Version
Clocks & Performance
Base Clock
Boost Clock
Memory Clock
Power Consumption
TDP/TGP
Recommended PSU
Power Connector
Additional
Slots
Release Date
Display Outputs
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H100 80Gb SXM (80GB)
NVIDIA
Флагманская GPU на архитектуре Hopper с 80 ГБ памяти HBM3 в форм-факторе SXM. Создана для обучения и инференса больших языковых моделей, HPC задач. Поддерживает FP64, FP32, TF32, FP16, BF16, FP8 и INT8 вычисления с Tensor Cores 4-го поколения.
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