Direct performance comparison between the RTX 4080 Super Pro and RTX 5090 across 21 standardized AI benchmarks collected from our production fleet. Testing shows the RTX 4080 Super Pro winning 1 out of 21 benchmarks (5% win rate), while the RTX 5090 wins 20 tests. All 21 benchmark results are automatically gathered from active rental servers, providing real-world performance data rather than synthetic testing.
In language model inference testing across 9 different models, the RTX 4080 Super Pro is 39% slower than the RTX 5090 on average. For deepseek-r1:32b inference, the RTX 4080 Super Pro reaches 34 tokens/s while the RTX 5090 achieves 71 tokens/s, making the RTX 4080 Super Pro substantially slower with a 53% deficit. Overall, the RTX 4080 Super Pro wins 1 out of 9 LLM tests with an average 40% performance difference, making the RTX 5090 the better option for LLM inference tasks.
Evaluating AI image generation across 12 different Stable Diffusion models, the RTX 4080 Super Pro is 36% slower than the RTX 5090 in this category. When testing sd3.5-medium, the RTX 4080 Super Pro completes generations at 9.1 s/image while the RTX 5090 achieves 4.5 s/image, making the RTX 4080 Super Pro substantially slower with a 51% deficit. Across all 12 image generation benchmarks, the RTX 4080 Super Pro wins 0 tests with an average 36% performance difference, making the RTX 5090 the better choice for Stable Diffusion, SDXL, and Flux workloads.
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Our benchmarks are collected automatically from servers having gpus of type RTX 4080 Super Pro and RTX 5090 in our fleet using standardized test suites:
Note: RTX 4080 Super Pro and RTX 5090 AI Benchmark Results may vary based on system load, configuration, and specific hardware revisions. These benchmarks represent median values from multiple test runs of RTX 4080 Super Pro and RTX 5090.
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