Direct performance comparison between the A100 and RTX 3090 across 20 standardized AI benchmarks collected from our production fleet. Testing shows the A100 winning 17 out of 20 benchmarks (85% win rate), while the RTX 3090 wins 3 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 performs nearly identically to the RTX 3090, with less than 10% average difference. For qwen3-coder:30b inference, the A100 reaches 115 tokens/s while the RTX 3090 achieves 132 tokens/s, making the A100 noticeably slower with a 13% deficit. Overall, the A100 wins 7 out of 8 LLM tests with an average 10% performance difference, making it the stronger choice for transformer model inference workloads.
Evaluating AI image generation across 12 different Stable Diffusion models, the A100 is 141% faster than the RTX 3090 in this category. When testing sd3.5-medium, the A100 completes generations at 8.9 images/min compared to RTX 3090's 2.1 images/min, making the A100 substantially faster with a 321% advantage. Across all 12 image generation benchmarks, the A100 wins 10 tests with an average 141% performance difference, establishing it as the preferred GPU for Stable Diffusion, SDXL, and Flux deployments.
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Our benchmarks are collected automatically from servers having gpus of type A100 and RTX 3090 in our fleet using standardized test suites:
Note: A100 and RTX 3090 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 3090.
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