RTX 5090
Consumer GPU based on Blackwell architecture with 32GB GDDR7 memory and 21,760 CUDA cores for AI workloads, machine learning, and image generation tasks.
GPU Benchmarks
RTX 4090 vs RTX 5090: RTX 5090 vs RTX 4090 Specs
Compare performance across LLMs and image models to find the best GPU for your workload.
RTX 4090 vs RTX 5090 specs for AI
Choose RTX 5090 when 32 GB of VRAM is the gating requirement. Choose RTX 4090 when 24 GB of VRAM is enough for the workload and availability or budget points that way.
| Spec | RTX 4090 | RTX 5090 | Source |
|---|---|---|---|
| VRAM | 24 GB GDDR6X | 32 GB GDDR7 | NVIDIA RTX 4090 specs, NVIDIA RTX 5090 specs |
| Memory interface | 384-bit | 512-bit | NVIDIA RTX 4090 specs, NVIDIA RTX 5090 specs |
| CUDA cores | 16,384 | 21,760 | NVIDIA RTX 4090 specs, NVIDIA RTX 5090 specs |
| NVLink support | No | No | NVIDIA RTX 4090 specs, NVIDIA RTX 5090 specs |
RTX 4090 vs RTX 5090 FAQ
Is the RTX 5090 better than the RTX 4090 for AI?
The RTX 5090 is the stronger fit when 32 GB of VRAM is required. The RTX 4090 remains a fit when the workload fits within 24 GB of VRAM.
How much VRAM do these GPUs have?
NVIDIA lists the RTX 4090 with 24 GB GDDR6X and the RTX 5090 with 32 GB GDDR7.
Do either of these GeForce cards support NVLink?
NVIDIA lists NVLink support as No for both RTX 4090 and RTX 5090.
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LLM inference benchmarks.
Benchmarks were run using vLLM in May 2025 with Runpod GPUs
RTX 4090
High-end consumer GPU based on Ada Lovelace architecture with 24GB GDDR6X memory and 16,384 CUDA cores for AI workloads, machine learning, and image generation tasks.
H100 PCIe
High-efficiency LLM processing at 90.98 tok/s.
Image generation benchmarks.
Benchmarks were run using Hugging Face Diffusers in May 2025 on Runpod GPUs.
H100 SXM
Unmatched image gen speed with 49.9 images per minute.
RTX 4090
AI image processing at 40.3 images per minute.
H100 PCIe
Pro-grade performance with 36 images per minute.
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Case Studies
Real-world GPU performance in action.
See how teams optimize cost and performance with the right GPU for their workloads.
"All of these projects, the renders for AMD, the Coca-Cola builds, that has to do with scalability. If we can't scale, we can't deliver. Runpod makes that possible."
"Runpod has changed the way we ship because we no longer have to wonder if we have access to GPUs. We've saved probably 90% on our infrastructure bill, mainly because we can use bursty compute whenever we need it."
"Runpod has allowed the team to focus more on the features that are core to our product and that are within our skill set, rather than spending time focusing on infrastructure, which can sometimes be a bit of a distraction.”
"Runpod helped us scale the part of our platform that drives creation. That’s what fuels the rest, image generation, sharing, remixing. It starts with training."
"Runpod allowed us to reliably handle scaling from zero to over 1,000 requests per second in our live application."
"Runpod has allowed us to focus entirely on growth and product development without us having to worry about the GPU infrastructure at all."
"We could stop worrying about infrastructure and go back to building. That’s the real win.”
Setup process was great—very quick and easy. Runpod had the exact GPUs we needed for inference and the pricing was very fair.
“The main value proposition for us was the flexibility Runpod offered. We were able to scale up effortlessly to meet the demand at launch.”
"After migration, we were able to cut down our server costs from thousands of dollars per day to only hundreds."
Runpod’s scalable GPU infrastructure gave us the flexibility we needed to match customer traffic and model complexity, without overpaying for idle resources.
