Direct performance comparison between the A100 and RTX 5090 across 20 standardized AI benchmarks collected from our production fleet. Testing shows the A100 winning 0 out of 20 benchmarks (0% win rate), while the RTX 5090 wins 20 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 A100 is 38% slower than the RTX 5090 on average. For llama3.1:8b inference, the A100 reaches 154 tokens/s while the RTX 5090 achieves 264 tokens/s, making the A100 substantially slower with a 42% deficit. Overall, the A100 wins 0 out of 8 LLM tests with an average 38% performance difference, making the RTX 5090 the better option for LLM inference tasks.
Evaluating AI image generation across 12 different Stable Diffusion models, the A100 is 26% slower than the RTX 5090 in this category. When testing sd3.5-medium, the A100 completes generations at 6.8 s/image while the RTX 5090 achieves 4.5 s/image, making the A100 significantly slower with a 34% deficit. Across all 12 image generation benchmarks, the A100 wins 0 tests with an average 26% 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 A100 and RTX 5090 in our fleet using standardized test suites:
Note: A100 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 A100 and RTX 5090.
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