Performance Rating
The Radeon RX 6800 3456SP was a high-end graphics card by AMD. Built on the 7 nm process, and based on the Navi 21 graphics processor, in its Navi 21 ES variant, the card supports DirectX 12 Ultimate. This ensures that all modern games will run on Radeon RX 6800 3456SP. Additionally, the DirectX 12 Ultimate capability guarantees support for hardware-raytracing, variable-rate shading and more, in upcoming video games. The Navi 21 graphics processor is a large chip with a die area of 520 mm² and 26,800 million transistors. Unlike the fully unlocked Radeon RX 6900 XT, which uses the same GPU but has all 5120 shaders enabled, AMD has disabled some shading units on the Radeon RX 6800 3456SP to reach the product's target shader count. It features 3456 shading units, 216 texture mapping units, and 96 ROPs. The card also has 54 raytracing acceleration cores. AMD has paired 16 GB GDDR6 memory with the Radeon RX 6800 3456SP, which are connected using a 256-bit memory interface. The GPU is operating at a frequency of 1700 MHz, which can be boosted up to 2250 MHz, memory is running at 2000 MHz (16 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
Recommended PSU
Power Connector
TDP/TGP
Rendering
Texture Units (TMU)
ROP
L2 Cache
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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