Direct performance comparison between the V100 and A100 across 12 standardized AI benchmarks collected from our production fleet. Testing shows the V100 winning 0 out of 12 benchmarks (0% win rate), while the A100 wins 12 tests. All 12 benchmark results are automatically gathered from active rental servers, providing real-world performance data rather than synthetic testing.
In language model inference testing across 4 different models, the V100 is 25% slower than the A100 on average. For gpt-oss:20b inference, the V100 reaches 113 tokens/s while the A100 achieves 149 tokens/s, making the V100 significantly slower with a 24% deficit. Overall, the V100 wins 0 out of 4 LLM tests with an average 25% performance difference, making the A100 the better option for LLM inference tasks.
Evaluating AI image generation across 8 different Stable Diffusion models, the V100 is 55% slower than the A100 in this category. When testing sdxl, the V100 completes generations at 9.8 images/min while the A100 achieves 23 images/min, making the V100 substantially slower with a 58% deficit. Across all 8 image generation benchmarks, the V100 wins 0 tests with an average 55% 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 V100 and A100 in our fleet using standardized test suites:
Note: V100 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 V100 and A100.
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