NVIDIA GeForce RTX 5080 Founders Edition Review With Copious Benchmarks
All of this data is brand new, using the latest build of Windows 11 (24H2), with the latest drivers and firmware available for all components as of the date of publication.
Our Test System Configuration:
| Hardware Used: AMD Ryzen 7 9800X3D (4.7GHz - 5.2GHz, 8-Core) MSI X870E Carbon WiFi 32GB G.SKILL DDR5-6000 Samsung SSD 990 Integrated Audio / Network Radeon RX 7900 XT GeForce RTX 4080 GeForce RTX 4090 GeForce RTX 5080 GeForce RTX 5090 Relevant Software: Windows 11 Pro 24H2 AMD Radeon v24.12.1 NVIDIA Drivers v571.86 / v571.12 |
Benchmarks Used: MLPerf Client Geekbench AI Procyon AI Text Generation Procyon AI Stable Diffusion XL Blender v4.3 Blackmagic RAW Speed Test v4.3.1 V-Ray UL 3DMark UL VRMark Unigine Superposition Assassin's Creed Mirage Black Myth Wukon Homeworld 3 Horizon Zero Dawn Remastered Cyberpunk 2077 (press beta) The Talos Principle II F1 24 |
MLPerf Client Benchmarks
The MLPerf Client benchmark was designed by MLCommons to evaluate machine learning inference tasks on PCs. It focuses on client form factors and aims to measure how well different hardware and software configurations handle four different AI workloads using a single model. It supports DirectML via ONNX Runtime for a wide range of hardware, but Intel also gets a specialized OpenVINO path for now. Participants in MLCommons are also able to optimize the models for their hardware, but must meet strict guidelines for accuracy.
The MLPerf Client benchmark had the GeForce RTX 5080 FE landing just behind the GeForce RTX 4090 and a few percentage points ahead of the GeForce RTX 4080. The RTX 5090 was way out in front, though.
The MLPerf Client benchmark had the GeForce RTX 5080 FE landing just behind the GeForce RTX 4090 and a few percentage points ahead of the GeForce RTX 4080. The RTX 5090 was way out in front, though.
Geekbench AI Testing
Geekbench AI is a cross-platform benchmark tool designed to evaluate the performance of AI workloads on a wide range devices, including smartphones, tablets, laptops, and desktops. It measures the performance of CPUs, GPUs, and NPUs (Neural Processing Units) across different operating systems like Android, iOS, Windows, macOS, and Linux with an array of machine learning tasks.
The GeForce RTX 5080 FE performed particularly well here. The updated cores in the GeForce RTX 5080 FE, along with that larger L1 cache and register file, and increased memory bandwidth, push it past the GeForce RTX 4090 and into second place, behind only the higher-end RTX 5090.
The GeForce RTX 5080 FE performed particularly well here. The updated cores in the GeForce RTX 5080 FE, along with that larger L1 cache and register file, and increased memory bandwidth, push it past the GeForce RTX 4090 and into second place, behind only the higher-end RTX 5090.
UL Procyon AI Text Generation Benchmarks
The Procyon AI Text Generation Benchmark is a tool developed by UL Solutions to evaluate the performance of large language models (LLMs) on Windows PCs. It features real-world use cases and uses seven prompts with both Retrieval-Augmented Generation (RAG) and non-RAG queries. It tests various AI models like Phi-3.5-mini, Mistral-7B, Llama-3.1-8B, and Llama-2-13B. These tests were run using ONNX with DirectML, not TensorRT, which is optimal for NVIDIA's RTX series discrete GPUs, but unavailable in this test at this time.
UL Procyon AI Text Generation GeForce RTX 5080 FE Details
With all four models, the GeForce RTX 5080 FE ends up being about 20% faster than the GeForce RTX 4080, but it's not enough to catch the RTX 4090 here.
In the hardware details posted above the charts, you can see the workloads are fairly bursty, and even under periods with sustained 100% GPU utilization, the GeForce RTX 5080 FE barely breaks the 60°C mark.
UL Procyon AI Text Generation GeForce RTX 5080 FE Details
With all four models, the GeForce RTX 5080 FE ends up being about 20% faster than the GeForce RTX 4080, but it's not enough to catch the RTX 4090 here.
In the hardware details posted above the charts, you can see the workloads are fairly bursty, and even under periods with sustained 100% GPU utilization, the GeForce RTX 5080 FE barely breaks the 60°C mark.
UL Procying Stable Diffusion XL AI Image Generation
The Procyon AI Image Generation Benchmark measures inference performance for image generation tasks. It includes several tests, with the Stable Diffusion XL (FP16) test we used here being the most demanding. The test is designed to evaluate a wide range of hardware from low power NPUs to high-end discrete GPUs and it can be configured to use different inference engines like NVIDIA TensorRT, Intel OpenVINO, and ONNX with DirectML. Unfortunately, the TensorRT engine hasn’t been updated for Blackwell just yet, but we tested it with ONNX to provide a point of reference versus the RTX 4090.
Like the LLM test above, this benchmark hasn't been updated to support TensorRT on Blackwell just yet, so the GeForce RTX 5080 FE is somewhat gimped by using ONNX and DirectML. We have both results on the RTX 40 series cards, however, to show the kind of uplift that will likely be possible on the new GeForce RTX 5080 FE when TensorRT is employed for optimal performance.
Like the LLM test above, this benchmark hasn't been updated to support TensorRT on Blackwell just yet, so the GeForce RTX 5080 FE is somewhat gimped by using ONNX and DirectML. We have both results on the RTX 40 series cards, however, to show the kind of uplift that will likely be possible on the new GeForce RTX 5080 FE when TensorRT is employed for optimal performance.
Blender v4.3 GPU Rendering Benchmarks
Blender is a free and open source 3D creation suite that can handle everything from modeling, rigging, and animation, through simulation, rendering, compositing, motion tracking, and even video editing or game creation. The developers offer a standalone benchmark tool that will track performance while rendering a handful of models. We used all three of the default models for these tests...
Depending on the particular model in use, the GeForce RTX 5080 FE performs right about on par with the RTX 4080 here, but well behind the RTX 4090. It was only with the Junkshop model that the GeForce RTX 5080 FE had a meaningful lead over the 4080.
V-Ray Rendering
The V-Ray Benchmark is a free tool that measures rendering performance on CPUs, NVIDIA GPUs, or a combination of both. The GPU benchmark in particular features a complex scene designed to evaluate the capabilities of both the RTX and CUDA-based V-Ray 6 render engines.
We tested V-Ray using the higher-performing RTX render engine, which put the GeForce RTX 5080 FE about 20% ahead of the GeForce RTX 4080 yet again.
Blackmagic RAW Speed Test Results
The Blackmagic RAW Speed Test is a CPU and GPU benchmarking tool that determines the speed of decoding full-resolution Blackmagic RAW video frames. The tool can be used to evaluate performance at various resolutions and bitrates on the CPU or using OpenCL or CUDA on a GPU. We're reporting four results here, at 8K and 4K resolutions, but at differing bitrates and compression levels.
At both resolutions, the GeForce RTX 4080 and RTX 5080 FE are evenly matched with the semi-compressed 3:1 RAW files, but this test is also affected by and often limited by system memory bandwidth. With the more compressed 12:1 data, the Blackwell-based GeForce RTX 5080 FE, with its newer media engine, pulls well ahead of the RTX 4080 and trails only the more powerful RTX 5090.
