Specifications Compared
| Spec | GB300 | RTX-4500-ADA |
|---|---|---|
| TDP | 1400W | 210W |
| VRAM | 288 GB | 24 GB |
| Memory Type | HBM3e | GDDR6 |
| Architecture | Blackwell Ultra | Ada Lovelace |
| Form Factors | SXM | PCIe |
| Interconnect | NVSwitch, NVLink | |
| FP8 Performance | 4,500 TFLOPS | |
| FP16 Performance | 2,250 TFLOPS | 39.6 TFLOPS |
| FP32 Performance | 90 TFLOPS | 39.6 TFLOPS |
| FP64 Performance | 45 TFLOPS | |
| INT8 Performance | 4,500 TOPS | 634 TOPS |
| Memory Bandwidth | 12,000 GB/s | 432 GB/s |
Performance Analysis
The GB300's FP16 performance of 2250 TFLOPS vastly outpaces the RTX 4500 Ada's 39.6 TFLOPS, signaling superior throughput for AI training where half-precision dominates. Its FP32 at 90 TFLOPS exceeds the RTX 4500 Ada's 39.6 TFLOPS, yet the real edge lies in FP8 at 4500 TFLOPS for inference tasks. This asymmetry optimizes the GB300 for deep learning pipelines, while the RTX 4500 Ada's balanced FP16 and FP32 suits graphics or general compute.
Memory specs define workload feasibility: 288 GB HBM3e versus 24 GB GDDR6 allows the GB300 to handle models with billions of parameters intact. The 12000 GB/s bandwidth supports massive batch sizes without bottlenecks, unlike the RTX 4500 Ada's 432 GB/s which constrains large-scale operations. In practice, this means faster convergence in training and higher inference throughput on the GB300.
Power draw reveals deployment realities. The GB300's 1400W TDP demands robust cooling and infrastructure, contrasting the RTX 4500 Ada's efficient 210W for edge or small-cluster use.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
RTX 4500 Ada
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA RTX 4500 Ada 24GB VRAM | 24GB | 0 vCPU 0GB RAM | 🌍global | $0.74/GPU/hr |
When to Choose the GB300
The GB300 excels in large-scale LLM training and inference requiring over 24 GB VRAM. Its 288 GB HBM3e and 12000 GB/s bandwidth enable processing of models like those exceeding 100 billion parameters with full batch sizes. NVLink and NVSwitch interconnects facilitate seamless multi-GPU clusters for distributed workloads.
Datacenter operators prioritize the GB300 for FP8 inference at 4500 TFLOPS, ideal for serving high-volume requests without precision loss.
When to Choose the RTX 4500 Ada
The RTX 4500 Ada suits cost-conscious users with its pricing from $0.34 per hour and average $0.51 per hour across three providers. Its 210W TDP fits standard PCIe workstations without specialized power setups. Balanced 39.6 TFLOPS FP16 and FP32 performance handles prototyping, fine-tuning smaller models, or graphics tasks within 24 GB GDDR6 limits.
Solo developers or small teams choose it for immediate availability and lower barriers versus the GB300's pending offers.
Use Cases
The GB300's 2250 TFLOPS FP16 and 288 GB HBM3e VRAM support massive models and large batches unattainable on the RTX 4500 Ada's 24 GB GDDR6.
FP8 performance at 4500 TFLOPS and 12000 GB/s bandwidth on the GB300 deliver high-throughput serving for large LLMs, far beyond the RTX 4500 Ada's 39.6 TFLOPS.
Fine-tuning demands substantial VRAM for parameter-efficient methods; the GB300's 288 GB handles full model loading unlike the RTX 4500 Ada's 24 GB limit.
Stable Diffusion fits within 24 GB GDDR6, leveraging the RTX 4500 Ada's 39.6 TFLOPS FP16 at $0.34 per hour for cost-effective image generation.
Balanced FP32 at 39.6 TFLOPS and low 210W TDP make the RTX 4500 Ada suitable for simulations; GB300's 1400W power is excessive for typical scientific loads.
Frequently Asked Questions
What is the VRAM difference between GB300 and RTX 4500 Ada?▾
The GB300 provides 288 GB HBM3e VRAM, while the RTX 4500 Ada offers 24 GB GDDR6. This 12-fold gap allows the GB300 to manage vastly larger models. Memory type enhances the GB300's speed for AI tasks.
How do memory bandwidths compare?▾
GB300 bandwidth reaches 12000 GB/s, compared to RTX 4500 Ada's 432 GB/s. This enables the GB300 to process larger batches without stalling. Higher bandwidth directly boosts training and inference efficiency.
What are the FP16 performance specs?▾
The GB300 delivers 2250 TFLOPS FP16, dwarfing the RTX 4500 Ada's 39.6 TFLOPS. This translates to faster AI training on the GB300. FP16 dominance suits modern deep learning workflows.
What is the power consumption of each GPU?▾
GB300 TDP is 1400W, requiring datacenter infrastructure, versus RTX 4500 Ada's 210W for standard setups. Lower power aids RTX 4500 Ada deployments. Efficiency varies by workload scale.
Are there current pricing offers for these GPUs?▾
RTX 4500 Ada starts at $0.34 per hour, averaging $0.51 per hour across three providers. GB300 has no live offers currently. Availability favors the RTX 4500 Ada for immediate use.
What architectures power these GPUs?▾
GB300 uses 2025 Blackwell Ultra for datacenter AI, while RTX 4500 Ada employs 2023 Ada Lovelace for workstations. Blackwell advances enable FP8 at 4500 TFLOPS. Ada balances general compute needs.
Which is cheaper to rent, the GB300 or the RTX 4500 Ada?▾
Cloud rental prices for both the GB300 and RTX 4500 Ada 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 4500 Ada?▾
The GB300 has 288 GB of HBM3e memory. The RTX 4500 Ada has 24 GB of GDDR6 memory.
Can I find GB300 and RTX 4500 Ada 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 4500 Ada?▾
The GB300 uses the Blackwell Ultra architecture (2025) while the RTX 4500 Ada uses Ada Lovelace (2023). The GB300 delivers 56.8x the FP16 throughput and 27.8x the memory bandwidth of the RTX 4500 Ada.