Direct performance comparison between the RTX 4080 Super Pro and A100 across 20 standardized AI benchmarks collected from our production fleet. Testing shows the RTX 4080 Super Pro winning 6 out of 20 benchmarks (30% win rate), while the A100 wins 14 tests. All 20 benchmark results are automatically gathered from active rental servers, providing real-world performance data rather than synthetic testing.
In language model inference testing across 8 different models, the RTX 4080 Super Pro performs nearly identically to the A100, with less than 10% average difference. For llama3.1:8b-instruct-q8_0 inference, the RTX 4080 Super Pro reaches 82 tokens/s while the A100 achieves 124 tokens/s, making the RTX 4080 Super Pro significantly slower with a 34% deficit. Overall, the RTX 4080 Super Pro wins 1 out of 8 LLM tests with an average 19% performance difference, making the A100 the better option for LLM inference tasks.
Evaluating AI image generation across 12 different Stable Diffusion models, the RTX 4080 Super Pro is 17% slower than the A100 in this category. When testing sdxl, the RTX 4080 Super Pro completes generations at 17 images/min while the A100 achieves 23 images/min, making the RTX 4080 Super Pro significantly slower with a 29% deficit. Across all 12 image generation benchmarks, the RTX 4080 Super Pro wins 5 tests with an average 17% performance difference, making the A100 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 A100 in our fleet using standardized test suites:
Note: RTX 4080 Super Pro and A100 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 A100.
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