This article is about the line of GPUs by Nvidia. For the original GeForce GPU, see GeForce 256.
For other uses, see G force (disambiguation).
Brand of GPUs by Nvidia
GeForce
Top: Logo since 2022 Bottom: The most recent flagship model, the GeForce RTX 4090, in the Founders Edition in its retail box
Release date
August 31, 1999; 24 years ago (1999-08-31)
Manufactured by
Nvidia
Samsung Electronics
TSMC
Designed by
Nvidia
Marketed by
Nvidia
Models
GeForce 256
GeForce 2 series
GeForce 3 series
GeForce 4 series
GeForce FX series
GeForce 6 series
GeForce 7 series
GeForce 8 series
GeForce 9 series
GeForce 100 series
GeForce 200 series
GeForce 300 series
GeForce 400 series
GeForce 500 series
GeForce 600 series
GeForce 700 series
GeForce 800 series
GeForce 900 series
GeForce 10 series
GeForce 16 series
GeForce 20 series
GeForce 30 series
GeForce 40 series
Cores
Up to 16,384 CUDA cores
Fabrication process
220 nm to 3 nm
History
Predecessor
RIVA TNT2
Variant
Nvidia Quadro, Nvidia Tesla
GeForce is a brand of graphics processing units (GPUs) designed by Nvidia and marketed for the performance market. As of the GeForce 40 series, there have been eighteen iterations of the design. The first GeForce products were discrete GPUs designed for add-on graphics boards, intended for the high-margin PC gaming market, and later diversification of the product line covered all tiers of the PC graphics market, ranging from cost-sensitive[1] GPUs integrated on motherboards, to mainstream add-in retail boards. Most recently,[when?] GeForce technology has been introduced into Nvidia's line of embedded application processors, designed for electronic handhelds and mobile handsets.
With respect to discrete GPUs, found in add-in graphics-boards, Nvidia's GeForce and AMD's Radeon GPUs are the only remaining competitors in the high-end market. GeForce GPUs are very dominant in the general-purpose graphics processor unit (GPGPU) market thanks to their proprietary Compute Unified Device Architecture (CUDA).[2] GPGPU is expected to expand GPU functionality beyond the traditional rasterization of 3D graphics, to turn it into a high-performance computing device able to execute arbitrary programming code in the same way a CPU does, but with different strengths (highly parallel execution of straightforward calculations) and weaknesses (worse performance for complex branching code).
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^https://drops.dagstuhl.com/opus/volltexte/2020/12373/pdf/LIPIcs-ECRTS-2020-10.pdf[permanent dead link] Dagstuhl
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