NVIDIA RTX 4000 Ada memory-bound vs compute-bound workloads

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NVIDIA RTX 4000 Ada delivers 107 FP16 TFLOPS and 26.7 FP32 TFLOPS, backed by 360 GB/s of memory bandwidth and 20 GB of VRAM. In mixed-precision fine-tuning, those numbers typically convert to solid throughput on dense models up to several tens of billions of parameters.

For low-latency inference, real-world tokens-per-second on common large language models depends more on memory bandwidth than peak FLOPS — the 360 GB/s figure is the relevant ceiling for autoregressive decoding. On batched workloads like diffusion image generation, compute becomes the dominant factor again.

At $0.76 per hour on the budget-friendly cloud provider, performance-per-dollar is competitive for AI-heavy workloads.

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