Performance Rating
The GeForce RTX 3050 A Mobile was a mobile graphics chip by NVIDIA, launched in 2024. Built on the 8 nm process, and based on the GA106 graphics processor, the chip supports DirectX 12 Ultimate. This ensures that all modern games will run on GeForce RTX 3050 A Mobile. Additionally, the DirectX 12 Ultimate capability guarantees support for hardware-raytracing, variable-rate shading and more, in upcoming video games. The GA106 graphics processor is an average sized chip with a die area of 276 mm² and 12,000 million transistors. Unlike the fully unlocked GeForce RTX 3060 3840SP, which uses the same GPU but has all 3840 shaders enabled, NVIDIA has disabled some shading units on the GeForce RTX 3050 A Mobile to reach the product's target shader count. It features 1792 shading units, 56 texture mapping units, and 32 ROPs. Also included are 56 tensor cores which help improve the speed of machine learning applications. The card also has 14 raytracing acceleration cores. NVIDIA has paired 4 GB GDDR6 memory with the GeForce RTX 3050 A Mobile, which are connected using a 128-bit memory interface. The GPU is operating at a frequency of 1065 MHz, which can be boosted up to 1343 MHz, memory is running at 1500 MHz (12 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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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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