NVIDIA RTX 5090 GPU: 32GB GDDR7 Specs, Pricing & Rental. Rent RTX 5090 GPU from $0.86/hr
32GB GDDR7, Blackwell architecture, 5th gen Tensor Cores. RTX 5090 GPU rentals deployed in under 2 minutes.
No long contracts · Per-minute billing · Deploy in ~2 minutes
You can rent an NVIDIA RTX 5090 on Spheron starting at $0.86/hr per GPU per hour on-demand, the lowest bookable on-demand rate on the marketplace. Per-minute billing, no contracts, deployed in under 2 minutes across data center partners in multiple regions. The RTX 5090 packs 32GB of GDDR7 memory and 5th gen Tensor Cores, making it the best price-to-performance choice for LoRA/QLoRA fine-tuning of 7B-13B models, Stable Diffusion XL inference, local LLM serving with Ollama or vLLM, and general AI development work. Launch a container with your CUDA/PyTorch image, SSH in, and start training in minutes.
NVIDIA RTX 5090 pricing
| Provider | Price/hr | Savings |
|---|---|---|
SpheronYour price | $0.86/hr | - |
CloudRift | $0.65/hr | - |
NeevCloud | $0.69/hr | - |
Runpod (Community) | $0.69/hr | - |
Runpod (Secure) | $0.99/hr | 1.2x more expensive |
NVIDIA RTX 5090 specifications
Need More RTX 5090 Than What's Listed?
Reserved Capacity
Commit to a duration, lock in availability and better rates
Custom Clusters
8 to 512+ GPUs, specific hardware, InfiniBand configs on request
Supplier Matchmaking
Spheron sources from its certified data center network, negotiates pricing, handles setup
Need more RTX 5090 capacity? Tell us your requirements and we'll source it from our certified data center network.
Typical turnaround: 24–48 hours
When to pick the RTX 5090
Pick RTX 5090 if
Your workload is LoRA/QLoRA fine-tuning on 7B-13B models, Stable Diffusion XL or Flux inference, or local LLM serving where 32GB VRAM is plenty. You want the cheapest Blackwell-generation GPU with 5th gen Tensor Cores and aren't bottlenecked by multi-GPU interconnect.
Pick RTX 4090 instead if
You need the absolute lowest hourly rate and 24GB VRAM is enough for your model. Your workload doesn't benefit from Blackwell's 2x AI throughput or the bandwidth jump from GDDR6X to GDDR7.
Pick RTX PRO 6000 instead if
You need 48GB or 96GB VRAM on Blackwell silicon to serve 30B+ quantized models on a single GPU, or you want pro-tier drivers and ECC memory for production workloads.
Pick H100 instead if
You're training or fine-tuning 30B+ parameter models end-to-end, need HBM3 bandwidth and NVLink/InfiniBand for multi-GPU, or your workload requires the Hopper FP8 Transformer Engine.
NVIDIA RTX 5090 use cases
AI Prototyping & Development
Rapidly iterate on AI models at low cost, making the RTX 5090 ideal for development workflows and early-stage experimentation.
Small Model Fine-Tuning
Perform LoRA and QLoRA fine-tuning of models up to 13B parameters with 32GB of fast GDDR7 memory.
Cost-Effective Inference
Deploy smaller models at minimal cost for production inference workloads that demand high throughput at a budget-friendly price.
AI Education & Research
Affordable GPU access for learning, research, and open-source contributions without the overhead of expensive data center GPUs.
NVIDIA RTX 5090 benchmarks
Serve Llama 3.1 8B on RTX 5090 with vLLM
Spin up an OpenAI-compatible inference endpoint on a single RTX 5090. The 32GB GDDR7 fits Llama 3.1 8B in FP16 with room for an 8K context window.
# SSH into your RTX 5090 instancessh root@<instance-ip> # Install vLLM (CUDA 12.x compatible)pip install vllm # Serve Llama 3.1 8B in FP16 on a single RTX 5090vllm serve meta-llama/Meta-Llama-3.1-8B-Instruct \ --dtype float16 \ --max-model-len 8192 \ --gpu-memory-utilization 0.9 \ --port 8000 # Test the OpenAI-compatible endpointcurl http://localhost:8000/v1/chat/completions \ -H "Content-Type: application/json" \ -d '{ "model": "meta-llama/Meta-Llama-3.1-8B-Instruct", "messages": [{"role": "user", "content": "Hello"}] }'RTX 5090 vs alternatives
RTX 5090 Guides & Benchmarks
More GPU Pricing guides →RTX 5090 Release Date and Cloud Availability
The NVIDIA GeForce RTX 5090 launched January 30, 2025 at $1,999 MSRP. NVIDIA announced the card at CES 2025 on January 7, 2025 as the flagship of the consumer Blackwell generation, with the RTX 5090 Founders Edition and AIB partner cards shipping later that month. The mobile RTX 5090 Laptop GPU followed in March 2025.
Cloud availability followed within weeks. Smaller GPU clouds were renting RTX 5090 by February 2025, with broader provider coverage by Q2 2025. On Spheron the RTX 5090 is available on-demand at per-minute billing with no contract, deployed across data center partners in North America, Europe, and Canada. Current availability and live pricing is on the pricing page. The RTX 5090 successor, NVIDIA's next-generation consumer card, has not been announced as of mid-2026.
RTX 5090 VRAM: 32GB GDDR7 Memory and Bandwidth
The RTX 5090 ships with 32GB of GDDR7 memory on a 512-bit bus, delivering 1.79 TB/s of memory bandwidth. That is a 33% VRAM increase and roughly 78% more bandwidth than the RTX 4090's 24GB GDDR6X at 1.01 TB/s. For AI workloads, the 32GB VRAM lets the RTX 5090 hold a 7B model in FP16 with an 8K context window, a 13B model in FP8 with room for a small batch, or a 30B model in INT4 with KV cache headroom for short context generation.
Where the 32GB VRAM matters most: LoRA and QLoRA fine-tuning of 7B-13B models, Stable Diffusion XL serving with ControlNet and a half-dozen LoRA adapters loaded, local LLM serving with Ollama or vLLM for sub-13B models, and AI development environments where the previous RTX 4090's 24GB VRAM was the bottleneck. For 70B-class models the RTX 5090's VRAM is insufficient even at INT4 quantization; the H100 SXM5 with 80GB HBM3 or H200 SXM5 with 141GB HBM3e is the right step up.
NVIDIA RTX 5090 FAQ
The RTX 5090 features the next-generation Blackwell architecture compared to the RTX 4090's Ada Lovelace. Key improvements include 32GB GDDR7 memory (vs 24GB GDDR6X on the 4090), approximately 2x AI performance, 5th generation Tensor Cores (vs 4th gen), and significantly higher memory bandwidth. The RTX 5090 delivers a substantial leap in AI workload performance while maintaining consumer-grade affordability.
The RTX 5090 is excellent for training small to medium models up to approximately 13B parameters. Its 32GB GDDR7 memory handles LoRA and QLoRA fine-tuning efficiently. For larger models requiring more VRAM or higher interconnect bandwidth, consider the H100 (80GB HBM3) or A100 (80GB HBM2e) for full-scale training workloads.
With 32GB of GDDR7, you can comfortably run Llama 3.1 8B (FP16, ~16GB), Mistral 7B (~14GB), Qwen 2.5 14B (FP16, marginal at ~28GB, needs context limits), Stable Diffusion XL, Flux.1 Dev, and Whisper Large V3. Quantized (Q4/INT4) versions of larger models such as Qwen 2.5 32B (~20GB) also fit. Llama 3.3 70B does not fit on a single RTX 5090 even at Q4; use an H100 or H200 for that class.
The H100 features 80GB HBM3 memory vs the RTX 5090's 32GB GDDR7, and is 2-3x faster for large-scale training workloads. However, the RTX 5090 is approximately 2x cheaper per hour and provides excellent performance for development, inference, and fine-tuning of smaller models. Choose the RTX 5090 for cost-effective development and the H100 for production-scale training.
Yes! The RTX 5090 features 4th generation RT Cores, making it excellent for real-time ray tracing, video editing, game development, and 3D rendering workloads. It is a versatile GPU that handles both AI/ML and creative professional workloads with outstanding performance.
All major deep learning frameworks are fully supported: PyTorch, TensorFlow, JAX, and ONNX Runtime. The RTX 5090 has full CUDA 12.x support, ensuring compatibility with the latest framework versions, libraries, and tools in the AI/ML ecosystem.
There's no minimum rental period! Spheron charges with per-minute billing granularity. Rent an RTX 5090 for as little as a few minutes to test your workload, or keep it running as long as you need. You only pay for what you use with no long-term contracts or commitments.
Yes, 32GB is well-suited for LoRA and QLoRA fine-tuning of models up to 13B parameters. Full fine-tuning works for 7B-class models. For full fine-tuning of larger models (30B+), consider the H100 with 80GB HBM3. The RTX 5090's fast GDDR7 memory also helps accelerate data loading during the fine-tuning process.
RTX 5090 GPUs are currently available in US, Europe, and Canada regions. We're continuously expanding capacity and availability. Check our app or contact sales for specific region requirements and current availability.
Our platform is plug-and-play for standard deployments. For 100+ GPU clusters, you get dedicated support via Slack or Discord, plus sourcing assistance. Enterprise customers get dedicated support channels and SLA guarantees.
Book a call with our teamYes. Spot is the interruptible tier of on-demand, priced up to 70% off the dedicated rate. Dedicated instances carry a 99.99% SLA and are non-interruptible; spot instances can be terminated when capacity is reclaimed by a dedicated workload. Key risks: job interruption during training/inference, loss of unsaved state, restart from last checkpoint. Best practices: checkpoint every 15-30 minutes, use spot for fault-tolerant or development workloads, save model weights to persistent storage, and run production serving on dedicated instances. Given the RTX 5090's already-low base price, spot makes it an exceptionally budget-friendly option for experimentation.