RTX 5090 vs RTX 4090: AI Performance Comparison
Is the RTX 5090 worth the upgrade? We compare SDXL, LLM inference, and overall AI performance between NVIDIA's flagship GPUs.
The Flagship Showdown
NVIDIA’s RTX 5090 has arrived, promising significant improvements over the already-excellent RTX 4090. But for AI workloads, is the $2,000 price tag justified?
Let’s dive into the numbers.
Specifications at a Glance
| Spec | RTX 5090 | RTX 4090 |
|---|---|---|
| Architecture | Blackwell | Ada Lovelace |
| VRAM | 32GB GDDR7 | 24GB GDDR6X |
| Memory Bandwidth | 1,792 GB/s | 1,008 GB/s |
| CUDA Cores | 21,760 | 16,384 |
| Tensor Cores | 680 | 512 |
| TDP | 575W | 450W |
| MSRP | $1,999 | $1,599 |
AI Benchmark Results
Stable Diffusion XL (1024x1024)
| GPU | Images/Minute | Improvement |
|---|---|---|
| RTX 5090 | 35 | +59% |
| RTX 4090 | 22 | baseline |
The RTX 5090 demolishes SDXL workloads, thanks to improved tensor cores and the jump to GDDR7 memory.
LLM Inference (7B Parameter Models)
| GPU | Tokens/Second | Improvement |
|---|---|---|
| RTX 5090 | 180 | +50% |
| RTX 4090 | 120 | baseline |
LLM Inference (13B Parameter Models)
| GPU | Tokens/Second | Improvement |
|---|---|---|
| RTX 5090 | 100 | +47% |
| RTX 4090 | 68 | baseline |
Maximum Model Size
The RTX 5090’s 32GB of VRAM is a game-changer:
- RTX 5090: Can run 70B parameter models with quantization
- RTX 4090: Limited to ~30B parameter models
This 8GB VRAM increase opens up entirely new use cases.
Power Consumption Reality
The elephant in the room is power draw:
- RTX 5090: 575W TDP (with spikes higher)
- RTX 4090: 450W TDP
This means:
- You’ll need a 1000W+ PSU
- Higher electricity costs over time
- More heat to dissipate
Efficiency Comparison (SDXL per Watt)
| GPU | Images/Min/100W |
|---|---|
| RTX 5090 | 6.09 |
| RTX 4090 | 4.89 |
Despite higher absolute power, the 5090 is actually more efficient per watt.
Value Analysis
New Card Value
| Metric | RTX 5090 | RTX 4090 |
|---|---|---|
| MSRP | $1,999 | $1,599 |
| SDXL $/img/min | $57 | $73 |
| LLM $/tok/s | $11 | $13 |
The RTX 5090 offers better value per performance unit despite the higher price.
vs Used RTX 4090
Many 4090s are available used for $1,500-1,700:
| Scenario | Cost | SDXL Value |
|---|---|---|
| 5090 New | $1,999 | $57/img/min |
| 4090 New | $1,899 | $86/img/min |
| 4090 Used | $1,650 | $75/img/min |
A used 4090 still represents excellent value for budget-conscious buyers.
Who Should Buy the RTX 5090?
Buy the RTX 5090 if:
- You need to run 70B+ parameter models locally
- Power cost isn’t a major concern
- You’re building a new system anyway
- You want future-proofing for larger models
Stick with the RTX 4090 if:
- 24GB VRAM meets your current needs
- You already own a 4090
- Power/heat are concerns
- You can find a good used deal
Skip Both if:
- Budget is under $1,500 (get a used 3090)
- You primarily run small models (RTX 4070 Ti Super)
Conclusion
The RTX 5090 is a genuine leap forward for AI workloads. The 32GB of GDDR7 memory and improved tensor cores deliver ~50% performance gains across the board.
However, for most users, a used RTX 4090 at $1,650 or even a used RTX 3090 at $700 offers far better value. The 5090 is best suited for professionals who need maximum VRAM and can justify the power costs.
Our Verdict: Wait for availability to normalize and prices to stabilize. If you need a card today, a used 4090 remains excellent.
Last updated: February 2025. Benchmarks based on early testing and may improve with driver updates.
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