Blackwell Architecture
Rent NVIDIA RTX 5090 Cloud GPU
The successor to the RTX 4090. 32GB GDDR7, 21,760 CUDA cores, Blackwell architecture, and ~1,792 GB/s memory bandwidth. The most powerful consumer GPU ever built for AI inference and creative workloads. Coming soon on VectorLay.
NVIDIA RTX 5090: Blackwell Comes to Consumer GPUs
The NVIDIA GeForce RTX 5090 is the flagship consumer GPU built on the Blackwell architecture, succeeding the enormously popular RTX 4090. It brings data center-class technology to a consumer form factor, with 32GB of GDDR7 memory—a 33% increase over the RTX 4090's 24GB GDDR7X—and a new memory subsystem delivering approximately 1,792 GB/s of bandwidth.
The jump to 32GB is significant for AI workloads. The RTX 4090's 24GB limit often forces users to quantize models or use reduced batch sizes. With 32GB, the RTX 5090 comfortably runs larger models at higher precision, fits bigger KV caches for inference serving, and enables training on datasets that previously required a data center GPU. For the growing number of 7B–13B models that define the sweet spot of local and cloud AI, the RTX 5090 is the ideal platform.
Beyond raw memory, the RTX 5090 features 21,760 CUDA cores (a 33% increase over the RTX 4090), 5th-generation Tensor Cores with Blackwell enhancements, and 105.1 TFLOPS of FP32 compute. The Blackwell architecture brings architectural improvements to AI workloads that make the RTX 5090 the most cost-effective GPU for inference at scale, provided your models fit within its 32GB memory envelope.
RTX 5090 Technical Specifications
| Specification | RTX 5090 |
|---|---|
| GPU Architecture | Blackwell (GB202) |
| VRAM | 32GB GDDR7 |
| CUDA Cores | 21,760 |
| Memory Bandwidth | ~1,792 GB/s |
| FP32 Performance | 105.1 TFLOPS |
| Shader TFLOPS | 170 TFLOPS |
| TDP | 575W |
| Memory Type | GDDR7 |
| Interface | PCIe Gen 5 |
| Tensor Cores | 5th Gen (Blackwell) |
The RTX 5090's Blackwell architecture introduces several improvements relevant to AI workloads. The 5th-generation Tensor Cores deliver higher throughput for mixed-precision operations, and the GDDR7 memory subsystem provides nearly 1.8x the bandwidth of the RTX 4090's GDDR7X. Combined with PCIe Gen 5 for faster host-to-device transfers, the RTX 5090 is a generational leap for consumer GPU compute.
RTX 5090 Cloud GPU Pricing
The RTX 5090 is newly launched and cloud GPU providers are still establishing pricing. As a reference, here's the current landscape:
| Provider | GPU | $/hour | Status |
|---|---|---|---|
| VectorLay | RTX 5090 | Coming soon | Waitlist open |
| RunPod | RTX 5090 | TBD | Not yet available |
| Lambda Labs | RTX 5090 | TBD | Not yet available |
| For reference | RTX 4090 (VectorLay) | $0.49 | Available now |
Based on historical pricing patterns and the RTX 5090's retail pricing, we expect cloud pricing to settle in the $0.69–$1.29/hr range once availability stabilizes. VectorLay will aim to offer the most competitive RTX 5090 pricing in the market. In the meantime, the RTX 4090 is available now at $0.49/hr for immediate deployment.
Best Use Cases for the RTX 5090
The RTX 5090 hits the sweet spot between consumer affordability and serious AI capability. With 32GB GDDR7 and Blackwell architecture, it excels at workloads that need more than 24GB but don't require data center HBM memory:
AI Inference (7B–13B Models)
Run Llama 3 8B, Mistral 7B, Gemma 2 9B, and similar models at full FP16 precision with room for large KV caches. The extra 8GB over the RTX 4090 allows higher batch sizes and longer context windows, directly translating to better throughput for production inference serving. Quantized 13B models also fit comfortably.
Image & Video Generation
Generate high-resolution images with Stable Diffusion XL, FLUX, and next-generation diffusion models. The 32GB VRAM enables higher-resolution outputs, larger batch sizes for parallel generation, and running the latest video generation models that exceed the RTX 4090's 24GB limit. The Blackwell architecture's improved Tensor Cores accelerate every step of the diffusion process.
Fine-Tuning & LoRA Training
Fine-tune 7B–13B parameter models with LoRA, QLoRA, or full fine-tuning. The RTX 5090's 32GB allows larger effective batch sizes during training, and the 105.1 TFLOPS of FP32 compute accelerates gradient calculations. For teams building domain-specific models, the RTX 5090 offers the best training performance per dollar.
Multi-Modal AI Applications
Deploy vision-language models like LLaVA, BLIP-2, and other multi-modal architectures that combine image encoders with language models. These models often exceed 24GB when loaded with both components, making the RTX 5090's 32GB a practical requirement. The Blackwell Tensor Cores efficiently handle both vision and language processing.
Cost-Effective Inference at Scale
For workloads that fit in 32GB, the RTX 5090 will offer dramatically better cost-per-token than data center GPUs. Running four RTX 5090s for the price of one H100 gives you 128GB of total VRAM and significantly higher aggregate throughput for embarrassingly parallel inference workloads. Ideal for startups and teams optimizing their inference cost structure.
Rapid Prototyping & Experimentation
The RTX 5090's combination of high compute, 32GB memory, and expected affordable cloud pricing makes it the ideal GPU for rapid iteration. Test new model architectures, evaluate different quantization strategies, benchmark inference frameworks, and prototype production deployments—all at a fraction of data center GPU costs.
How to Get Access to the RTX 5090 on VectorLay
VectorLay is bringing RTX 5090 GPUs online as soon as supply allows. Here's how to get early access:
Join the waitlist
Visit vectorlay.com/contact to join the RTX 5090 waitlist. Share your use case so we can prioritize the right configurations and capacity.
Get notified on availability
We'll reach out as soon as RTX 5090 instances are live with confirmed pricing. Waitlist members get first access and potential introductory pricing.
Deploy with bare-metal performance
Like every GPU on VectorLay, the RTX 5090 will use VFIO passthrough for full bare-metal performance. The complete 32GB GDDR7 and all 21,760 CUDA cores are exclusively yours—no GPU sharing, no virtualization overhead. Bring any Docker image and deploy in minutes.
Use RTX 4090s in the meantime
While waiting for the RTX 5090, VectorLay offers RTX 4090 GPUs at just $0.49/hr. With 24GB GDDR7X and Ada Lovelace architecture, the RTX 4090 handles many of the same workloads. Start building and testing your pipelines today and migrate to the RTX 5090 when it's available.
RTX 5090 vs RTX 4090: A Generational Leap
The RTX 5090 builds on the RTX 4090's legacy as the best consumer GPU for AI with meaningful upgrades across every specification:
| Feature | RTX 5090 | RTX 4090 |
|---|---|---|
| Architecture | Blackwell | Ada Lovelace |
| VRAM | 32GB GDDR7 | 24GB GDDR7X |
| Memory Bandwidth | ~1,792 GB/s | 1,008 GB/s |
| CUDA Cores | 21,760 | 16,384 |
| FP32 Performance | 105.1 TFLOPS | 82.6 TFLOPS |
| TDP | 575W | 450W |
| PCIe | Gen 5 | Gen 4 |
| VectorLay Price | Coming soon | $0.49/hr |
The RTX 5090 delivers roughly 33% more CUDA cores, 33% more VRAM, 78% more memory bandwidth, and 27% more FP32 compute than the RTX 4090. For AI inference, the memory bandwidth improvement is the most impactful—LLM token generation is almost always memory-bandwidth limited, so the 1,792 GB/s of GDDR7 bandwidth translates directly to faster inference speeds. The extra 8GB of VRAM also opens up models and batch sizes that were previously out of reach on the RTX 4090.
RTX 5090 Performance for AI Workloads
Based on the RTX 5090's specifications and early benchmarks, here are expected performance characteristics for common AI workloads:
| Workload | Model | RTX 5090 vs RTX 4090 |
|---|---|---|
| LLM Inference | Llama 3 8B (FP16) | ~1.5–1.8x faster |
| LLM Inference | Mistral 7B (FP16) | ~1.5–1.8x faster |
| Image Generation | SDXL (30 steps, 1024x1024) | ~1.3–1.5x faster |
| Fine-Tuning | 7B LoRA fine-tune | ~1.3–1.5x faster |
| Batch Throughput | Llama 3 8B (continuous batching) | Higher batch sizes (32GB) |
The RTX 5090's performance gains come from three sources: more CUDA and Tensor Cores for higher raw compute, GDDR7 for dramatically higher memory bandwidth, and 32GB of VRAM for larger models and batch sizes. For memory-bandwidth-bound workloads like LLM inference, the ~78% bandwidth increase is the primary driver of the speedup. For compute-bound workloads like training and image generation, the 33% increase in CUDA cores and Blackwell architectural improvements contribute to meaningful but more modest gains.
Frequently Asked Questions
How much will it cost to rent an RTX 5090 in the cloud?
Cloud RTX 5090 pricing is not yet established as the GPU is newly released and providers are still ramping up availability. Based on the RTX 4090's cloud pricing ($0.49–$0.74/hr across major providers), we expect RTX 5090 cloud pricing to land in the $0.69–$1.29/hr range once supply stabilizes. VectorLay will announce competitive pricing when availability is confirmed—join the waitlist to be notified.
What is the difference between the RTX 5090 and RTX 4090?
The RTX 5090 is a generational upgrade over the RTX 4090. Key improvements include: 32GB GDDR7 memory (vs 24GB GDDR7X), Blackwell architecture (vs Ada Lovelace), 21,760 CUDA cores (vs 16,384), ~1,792 GB/s memory bandwidth (vs 1,008 GB/s), and 105.1 TFLOPS FP32 (vs 82.6 TFLOPS). The 33% increase in VRAM is especially significant for AI inference, allowing larger models to fit without quantization.
What AI models can run on the RTX 5090?
With 32GB GDDR7, the RTX 5090 can run larger models than the RTX 4090 without quantization. It comfortably handles Llama 3 8B at FP16, Mistral 7B, Stable Diffusion XL, and many 13B models with quantization. The extra 8GB over the RTX 4090 also allows for larger batch sizes and longer context windows when serving smaller models. For the absolute largest models (70B+), you'll still want an H100 or H200 with HBM memory.
When will the RTX 5090 be available on VectorLay?
VectorLay is working to bring RTX 5090 GPUs to the platform as supply becomes available. The RTX 5090 has launched at retail, and we are actively sourcing units for our cloud infrastructure. Join the waitlist at vectorlay.com/contact to be the first to know when RTX 5090 instances go live, along with confirmed pricing.
Is the RTX 5090 good for AI training?
The RTX 5090 is excellent for training small to medium models (up to ~13B parameters with appropriate precision). Its 32GB GDDR7 memory and high FP32 throughput (105.1 TFLOPS) make it ideal for fine-tuning 7B–13B models, training custom LoRA adapters, and experimenting with new architectures. For large-scale training of 70B+ models, data center GPUs like the H100 with HBM memory and NVLink are more appropriate.
How does the RTX 5090 compare to data center GPUs like the H100?
The RTX 5090 and H100 serve different segments. The RTX 5090 offers exceptional price-to-performance for models that fit in 32GB VRAM—expected to be well under $1/hr in the cloud vs $2.49/hr for the H100. However, the H100's 80GB HBM3 with 3,350 GB/s bandwidth is essential for large models and high-throughput serving. Choose the RTX 5090 when your models fit in 32GB; choose the H100 when you need more memory, bandwidth, or multi-GPU NVLink scaling.
Ready for Blackwell performance?
The RTX 5090 is coming to VectorLay. Join the waitlist to get priority access and be the first to deploy on the most powerful consumer GPU ever built. In the meantime, the RTX 4090 is available now at $0.49/hr.