Performance Rating
The GeForce 9600 GSO was a graphics card by NVIDIA, launched on April 28th, 2008. Built on the 65 nm process, and based on the G92 graphics processor, the card supports DirectX 11.1. Even though it supports DirectX 11, the feature level is only 10_0, which can be problematic with many DirectX 11 & DirectX 12 titles. The G92 graphics processor is a large chip with a die area of 324 mm² and 754 million transistors. Unlike the fully unlocked GeForce 8800 GTS 512, which uses the same GPU but has all 128 shaders enabled, NVIDIA has disabled some shading units on the GeForce 9600 GSO to reach the product's target shader count. It features 96 shading units, 48 texture mapping units, and 12 ROPs. NVIDIA has paired 384 MB GDDR3 memory with the GeForce 9600 GSO, which are connected using a 192-bit memory interface. The GPU is operating at a frequency of 550 MHz, memory is running at 800 MHz.
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
Recommendations
Эта видеокарта хорошо подходит для базового рендеринга и научных вычислений. Из-за старой архитектуры Tesla и низкой пропускной способности она не рекомендована для современной машинного обучения или глубокого обучения. Для игр и офисных задач она также слишком слаба.
Renting is cheaper than buying
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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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