Direct performance comparison between the RTX 4070 Ti Super and RTX Pro 6000 Blackwell across 17 standardized AI benchmarks collected from our production fleet. Testing shows the RTX 4070 Ti Super winning 1 out of 17 benchmarks (6% win rate), while the RTX Pro 6000 Blackwell wins 16 tests. 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 RTX 4070 Ti Super is 89% slower than the RTX Pro 6000 Blackwell (median across 2 benchmarks). For nvidia/Llama-3.1-8B-Instruct-FP8, the RTX 4070 Ti Super reaches 230 tokens/s while RTX Pro 6000 Blackwell achieves 1997 tokens/s (88% slower). The RTX 4070 Ti Super wins none out of 2 high-throughput tests, making the RTX Pro 6000 Blackwell better suited for production API workloads.
For personal AI assistants and local development with one request at a time, the RTX 4070 Ti Super is 43% slower than the RTX Pro 6000 Blackwell (median across 3 benchmarks). Running qwen3:8b, the RTX 4070 Ti Super generates 99 tokens/s while RTX Pro 6000 Blackwell achieves 174 tokens/s (43% slower). The RTX 4070 Ti Super wins none out of 3 single-user tests, making the RTX Pro 6000 Blackwell the better choice for local AI development.
For Stable Diffusion, SDXL, and Flux workloads, the RTX 4070 Ti Super is 53% slower than the RTX Pro 6000 Blackwell (median across 8 benchmarks). Testing sdxl, the RTX 4070 Ti Super completes at 14 images/min while RTX Pro 6000 Blackwell achieves 33 images/min (59% slower). The RTX 4070 Ti Super wins none out of 8 image generation tests, making the RTX Pro 6000 Blackwell the better choice for Stable Diffusion workloads.
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Our benchmarks are collected automatically from servers having GPUs of type RTX 4070 Ti Super and RTX Pro 6000 Blackwell 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 RTX 4070 Ti Super and RTX Pro 6000 Blackwell 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 RTX 4070 Ti Super and RTX Pro 6000 Blackwell 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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