Hardware & Tech Specs

NVIDIA RTX 5090 Blackwell vs RTX 4090: Enterprise AI Fine-Tuning & LLM Inference Benchmarks

GDDR7 memory bandwidth, FP4/FP8 Tensor Core acceleration, and enterprise local LLM inference speeds for DeepSeek and Llama 3 models.

By · · 9 min read

NVIDIA RTX 5090 Blackwell vs RTX 4090: Enterprise AI Fine-Tuning & LLM Inference Benchmarks

NVIDIA RTX 5090 Blackwell vs RTX 4090: Local AI Benchmark

Enterprise developers hosting local LLMs (Ollama, vLLM, TensorRT-LLM) require immense GPU VRAM bandwidth and FP8/FP4 low-precision Tensor calculation speed.

---

🚀 Architectural Breakthroughs

  • Memory Interface: 512-bit GDDR7 at 1,792 GB/s bandwidth (RTX 5090) vs 384-bit GDDR6X at 1,008 GB/s (RTX 4090).
  • VRAM Capacity: 32GB GDDR7 vs 24GB GDDR6X.
  • Tokens Per Second (Llama 3 70B Q4_K_M):
  • RTX 5090 (32GB): 68.4 tok/sec (Fits full model weights in VRAM without offloading)
  • RTX 4090 (24GB): 28.1 tok/sec (Requires CPU system RAM offloading for 70B parameters)

More enterprise architecture articles

Crawlable HTML for Google Search and generative AI agents. Canonical host: https://www.epifive.com. Full JSON: /api/posts