Direct performance comparison between the A100 and RTX 4070 Ti Super across 16 standardized AI benchmarks collected from our production fleet. Testing shows the A100 winning all 16 out of 16 benchmarks, while the RTX 4070 Ti Super has no wins. All benchmark results are automatically gathered from active rental servers, providing real-world performance data.
For production API servers and multi-agent AI systems running multiple concurrent requests, the A100 is 242% faster than the RTX 4070 Ti Super (median across 1 benchmarks). For Qwen/Qwen3-4B, the A100 achieves 832 tokens/s vs RTX 4070 Ti Super's 243 tokens/s (242% faster). The A100 wins 1 out of 1 high-throughput tests, making it the stronger choice for production chatbots and batch processing.
For personal AI assistants and local development with one request at a time, the A100 is 27% faster than the RTX 4070 Ti Super (median across 3 benchmarks). Running qwen3:8b, the A100 generates 126 tokens/s vs RTX 4070 Ti Super's 99 tokens/s (27% faster). The A100 wins 3 out of 3 single-user tests, making it ideal for personal coding assistants and prototyping.
For Stable Diffusion, SDXL, and Flux workloads, the A100 is 81% faster than the RTX 4070 Ti Super (median across 8 benchmarks). Testing sd1.5, the A100 completes at 0.92 s/image vs RTX 4070 Ti Super's 1.7 s/image (84% faster). The A100 wins 8 out of 8 image generation tests, making it the preferred GPU for AI art and image generation.
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Our benchmarks are collected automatically from servers having GPUs of type A100 and RTX 4070 Ti Super in our fleet. Unlike synthetic lab tests, these results come from real production servers handling actual AI workloads - giving you transparent, real-world performance data.
We test both vLLM (High-Throughput) and Ollama (Single-User) frameworks. vLLM benchmarks show how A100 and RTX 4070 Ti Super perform with 16-64 concurrent requests - perfect for production chatbots, multi-agent AI systems, and API servers. Ollama benchmarks measure single-request speed for personal AI assistants and local development. Models tested include Llama 3.1, Qwen3, DeepSeek-R1, and more.
Image generation benchmarks cover Flux, SDXL, and SD3.5 architectures. That's critical for AI art generation, design prototyping, and creative applications. Focus on single prompt generation speed to understand how A100 and RTX 4070 Ti Super handle your image workloads.
We also include CPU compute power (affecting tokenization and preprocessing) and NVMe storage speeds (critical for loading large models and datasets) - the complete picture for your AI workloads.
Note: Results may vary based on system load and configuration. These benchmarks represent median values from multiple test runs.
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