Best Pick

MSI GeForce RTX 5090 SUPRIM Liquid 32GB GDDR7

80.3 Workstation Score
GeForce RTX 509032GB GDDR7512-bit600W
Why we recommend this

The 32GB GDDR7 VRAM on a 512-bit interface, paired with 21,760 CUDA cores and a 2580MHz boost clock, delivers top-tier 4K gaming and ray tracing performance. Its hybrid AIO liquid cooling keeps the card compact at 148mm, fitting into smaller cases while maintaining high power efficiency. This GPU is best for enthusiasts building a high-end 4K gaming rig or creators needing massive VRAM for AI workloads.

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Great Alternatives

These options also score highly and may better suit your specific needs

Gigabyte GV-N5090WF3OC-32GD

78.3 Workstation Score
GeForce RTX 509032GB GDDR7512-bit575W
Why we recommend this ▼

The 21,760 CUDA cores and 2467MHz boost clock on the Blackwell RTX 5090 deliver top-tier 4K gaming and AI performance, backed by 32GB of GDDR7 memory on a 512-bit interface. The triple-fan WINDFORCE cooling keeps the 575W TDP in check, while DLSS 4 and AV1 encoding add value for creators and gamers alike. Best for enthusiasts running 4K ray-traced titles or local LLM workloads who need the fastest consumer GPU available.

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ZOTAC GeForce RTX 5090 SOLID OC 32GB GDDR7

76.9 Workstation Score
GeForce RTX 509032GB GDDR7512-bit575W
Why we recommend this ▼

The 32GB of GDDR7 memory and 21,760 CUDA cores on the Blackwell architecture deliver a 38,845 PassMark G3D score for uncompromised 4K gaming and AI workloads. Its IceStorm 3.0 cooler with a 34% larger vapor chamber and reinforced metal mid-frame ensures sustained boost clocks under the 575W TDP without excessive noise. This card is best for AI researchers running large language models and 4K gamers who demand maximum frame rates with ray tracing and DLSS 4.

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NVIDIA Blackwell GPU Jetson Thor 128GB workstation

52.9 Workstation Score
NVIDIA Blackwell GPU128GB
Why we recommend this ▼

Equipped with a 2560-core NVIDIA Blackwell GPU and 96 fifth-gen Tensor Cores, this developer kit delivers 2070 TFLOPS of AI performance for demanding model training. The 128GB memory pool and dedicated AI acceleration make it a specialized tool for edge computing and robotics prototyping. This kit is best for AI researchers and robotics engineers developing and deploying large language models directly on-device.

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