Direct performance comparison between the V100 and RTX 3090 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 RTX 3090 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 17% slower than the RTX 3090 on average. For qwen3:8b inference, the V100 reaches 99 tokens/s while the RTX 3090 achieves 122 tokens/s, making the V100 noticeably slower with a 19% deficit. Overall, the V100 wins 0 out of 4 LLM tests with an average 17% performance difference, making the RTX 3090 the better option for LLM inference tasks.
Evaluating AI image generation across 8 different Stable Diffusion models, the V100 is 23% slower than the RTX 3090 in this category. When testing sd3.5-medium, the V100 completes generations at 43 s/image while the RTX 3090 achieves 31 s/image, making the V100 significantly slower with a 28% deficit. Across all 8 image generation benchmarks, the V100 wins 0 tests with an average 23% performance difference, making the RTX 3090 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 RTX 3090 in our fleet using standardized test suites:
Note: V100 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 V100 and RTX 3090.
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