Specifications Compared
| Spec | GB300 | RTX-3090 |
|---|---|---|
| TDP | 1400W | 350W |
| VRAM | 288 GB | 24 GB |
| Memory Type | HBM3e | GDDR6X |
| Architecture | Blackwell Ultra | Ampere |
| Form Factors | SXM | PCIe |
| Interconnect | NVSwitch, NVLink | NVLink |
| FP8 Performance | 4,500 TFLOPS | |
| FP16 Performance | 2,250 TFLOPS | 35.6 TFLOPS |
| FP32 Performance | 90 TFLOPS | 35.6 TFLOPS |
| FP64 Performance | 45 TFLOPS | |
| INT8 Performance | 4,500 TOPS | |
| Memory Bandwidth | 12,000 GB/s | 936 GB/s |
Performance Analysis
The GB300's FP16 throughput of 2250 TFLOPS vastly outpaces the RTX 3090's 35.6 TFLOPS, accelerating AI training where half-precision dominates. FP32 performance shows a narrower lead at 90 TFLOPS versus 35.6 TFLOPS, benefiting general compute but emphasizing the GB300's AI focus. The FP8 capability of 4500 TFLOPS on the GB300 enables ultra-efficient inference for massive language models, unavailable on the RTX 3090. Memory bandwidth of 12000 GB/s on the GB300 supports enormous batch sizes in training, reducing iterations compared to the RTX 3090's 936 GB/s limitation, which constrains large-model handling. In real-world terms, the GB300 handles datasets fitting 288 GB VRAM seamlessly, while the RTX 3090 requires model parallelism at 24 GB. Power draw reflects this: 1400W TDP for the GB300 demands robust cooling via SXM form factor, versus the RTX 3090's efficient 350W in PCIe setups. NVSwitch on the GB300 enhances multi-GPU scaling over the RTX 3090's NVLink.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
RTX 3090
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 TensorDock | NVIDIA GeForce RTX 3090 24GB VRAM | 24GB | 0 vCPU 0GB RAM | Wilmington, Delaware | $0.20/GPU/hr | Available | ||
TensorDock | NVIDIA GeForce RTX 3090 24GB VRAM | 24GB | 0 vCPU 0GB RAM | Dallas, Texas | $0.21/GPU/hr | Available | ||
 Vast.ai | 4×NVIDIA GeForce RTX 3090 24GB VRAM | 24GB | 32 vCPU 403GB RAM 104GB Storage | Iceland | $0.25/GPU/hr $1.01/hr total (4×) | Available | ||
Vast.ai | 4×NVIDIA GeForce RTX 3090 24GB VRAM | 24GB | 32 vCPU 252GB RAM 1217GB Storage | Finland | $0.27/GPU/hr $1.07/hr total (4×) | Available | ||
 LeaderGPU | 8×NVIDIA GeForce RTX 3090 24GB VRAM | 24GB | 64 vCPU 384GB RAM 2000GB Storage | Netherlands | $0.29/GPU/hr $2.29/hr total (8×) | Available |
When to Choose the GB300 SXM6
The NVIDIA GB300 excels in large-scale LLM training and inference requiring over 24 GB VRAM. Its 288 GB HBM3e and 12000 GB/s bandwidth handle massive batch sizes without fragmentation. FP8 at 4500 TFLOPS suits quantized inference for production deployments.
When to Choose the RTX 3090
The NVIDIA GeForce RTX 3090 suits budget-conscious users with 45 live cloud offers from $0.08 per hour. It performs adequately for fine-tuning models under 24 GB VRAM and Stable Diffusion tasks at 35.6 TFLOPS FP16. Lower 350W TDP and PCIe compatibility ease integration in smaller clusters.
Use Cases
The GB300's 288 GB VRAM and 2250 TFLOPS FP16 support training massive models without sharding. RTX 3090's 24 GB limits it to small-scale efforts.
FP8 performance of 4500 TFLOPS on the GB300 delivers high-throughput quantized inference. RTX 3090 cannot match this efficiency.
RTX 3090 handles fine-tuning under 24 GB VRAM at 35.6 TFLOPS FP16 with low cost from $0.08 per hour. GB300 overkill for smaller tasks.
RTX 3090's 24 GB GDDR6X suffices for image generation at 936 GB/s bandwidth. Affordable cloud access across 45 offers.
GB300's 90 TFLOPS FP32 and 12000 GB/s bandwidth accelerate simulations with large datasets. RTX 3090's specs constrain complex workloads.
Frequently Asked Questions
What is the VRAM difference between GB300 and RTX 3090?▾
The GB300 offers 288 GB HBM3e VRAM, compared to the RTX 3090's 24 GB GDDR6X. This 12-fold increase allows the GB300 to load enormous models entirely in memory. RTX 3090 users often need techniques like gradient checkpointing.
How does memory bandwidth compare?▾
GB300 provides 12000 GB/s bandwidth, over 12 times the RTX 3090's 936 GB/s. Higher bandwidth on GB300 reduces data bottlenecks in training. This impacts batch sizes directly.
What are the FP16 performance figures?▾
GB300 achieves 2250 TFLOPS in FP16, versus RTX 3090's 35.6 TFLOPS. The gap translates to roughly 63 times faster AI training on GB300. Inference benefits similarly.
Is RTX 3090 cheaper in the cloud?▾
RTX 3090 rentals start at $0.08 per hour across 45 offers, averaging $0.44 per hour. GB300 has no live offers currently. This makes RTX 3090 practical for immediate use.
What are the power requirements?▾
GB300 demands 1400W TDP in SXM form factor, requiring datacenter infrastructure. RTX 3090 uses 350W in PCIe, suitable for standard servers. Efficiency favors RTX 3090 for small setups.
Which supports better multi-GPU scaling?▾
GB300 uses NVSwitch and NVLink for superior multi-GPU performance. RTX 3090 relies on NVLink alone. This enables larger effective clusters on GB300.
Which is cheaper to rent, the GB300 or the RTX 3090?▾
Cloud rental prices for both the GB300 and RTX 3090 vary by provider, configuration, and availability. This page shows live pricing from 25+ providers updated every 60 seconds. Scroll to the Live Cloud Pricing section to compare current rates.
How much VRAM does the GB300 have compared to the RTX 3090?▾
The GB300 has 288 GB of HBM3e memory. The RTX 3090 has 24 GB of GDDR6X memory.
Can I find GB300 and RTX 3090 GPUs available to rent right now?▾
Yes. This page shows real-time availability across 25+ cloud GPU providers. The Live Cloud Pricing section displays only in-stock offers with current pricing.
What is the main difference between the GB300 and the RTX 3090?▾
The GB300 uses the Blackwell Ultra architecture (2025) while the RTX 3090 uses Ampere (2020). The GB300 delivers 63.2x the FP16 throughput and 12.8x the memory bandwidth of the RTX 3090.