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Versus Engine

Nvidia GeForce RTX 5090 (32GB) vs Threadripper Pro + Dual RTX 4090 Build

Specs, price and the one trade-off that actually decides it — Nvidia GeForce RTX 5090 (32GB) against Threadripper Pro + Dual RTX 4090 Build, side by side.

Cheaper to start

Tie

Both start at a similar price.

Rated higher

Nvidia GeForce RTX 5090 (32GB)

9.7 vs 9.2 on our design scale.

Standout

Nvidia GeForce RTX 5090 (32GB)

32GB GDDR7 — runs 70B-class models quantised on a single card

Nvidia GeForce RTX 5090 (32GB)

Nvidia GeForce RTX 5090 (32GB)

The fastest consumer card available, with 32GB of GDDR7 — and the power bill to match.

Where it wins, where it doesn't

Pros

  • 32GB GDDR7 — runs 70B-class models quantised on a single card
  • Fastest consumer silicon available
  • Avoids the complexity of a multi-GPU build

Cons

  • Roughly double the 5080's price for far less than double the performance
  • 600W-class power delivery dictates case and PSU choices
  • Poor value for anything that is not memory-bound

Specifications

  • memory32GB GDDR7
  • cuda_cores21760
  • memory_bus512-bit
  • architectureBlackwell
  • recommended_psu1000W
  • memory_bandwidth1792 GB/s
  • total_graphics_power575W
  • cpu
  • gpu
  • tier
  • ram_gb
  • vram_gb_total
  • example_models
  • tokens_per_second
Threadripper Pro + Dual RTX 4090 Build

Threadripper Pro + Dual RTX 4090 Build

Professional-tier workstation: AMD Ryzen Threadripper Pro with two NVIDIA GeForce RTX 4090s (48 GB VRAM total) and 256 GB of RAM. Runs Llama 3.1 405B and gpt-oss-120b at roughly 10-20 tokens/s — the enterprise end of this index for on-premises inference.

Where it wins, where it doesn't

Pros

  • 48GB total VRAM for heavy inference
  • Massive PCIe lane bandwidth
  • 64-core compute headroom

Cons

  • Extreme power consumption (1500W+ peak)
  • High noise levels under sustained load

Specifications

  • memory
  • cuda_cores
  • memory_bus
  • architecture
  • recommended_psu
  • memory_bandwidth
  • total_graphics_power
  • cpuAMD Ryzen Threadripper Pro
  • gpu2x NVIDIA GeForce RTX 4090
  • tierprofessional
  • ram_gb256
  • vram_gb_total48
  • example_modelsLlama 3.1 405B, gpt-oss-120b
  • tokens_per_second10-20