Specifications Compared
| Spec | GB300 | RTX-5060 |
|---|---|---|
| TDP | 1400W | 180W |
| VRAM | 288 GB | 12 GB |
| Memory Type | HBM3e | GDDR7 |
| Architecture | Blackwell Ultra | Blackwell |
| Form Factors | SXM | PCIe |
| Interconnect | NVSwitch, NVLink | |
| FP8 Performance | 4,500 TFLOPS | |
| FP16 Performance | 2,250 TFLOPS | 23.1 TFLOPS |
| FP32 Performance | 90 TFLOPS | 23.1 TFLOPS |
| FP64 Performance | 45 TFLOPS | |
| INT8 Performance | 4,500 TOPS | 370 TOPS |
| Memory Bandwidth | 12,000 GB/s | 448 GB/s |
Performance Analysis
Compute disparities define real-world capabilities between the GB300 and RTX 5060. The GB300's 2250 TFLOPS FP16 vastly outpaces its 90 TFLOPS FP32, optimizing mixed-precision training and inference for large language models where FP16 dominates. The RTX 5060 balances at 23.1 TFLOPS for both FP16 and FP32, suiting graphics rendering or smaller AI tasks but limiting throughput on demanding workloads.
Memory bandwidth profoundly impacts batch sizes and model scale: GB300's 12000 GB/s supports massive datasets and untruncated batches in 288 GB VRAM, reducing overhead in distributed training. RTX 5060's 448 GB/s and 12 GB VRAM constrain it to smaller models, often requiring quantization or multi-GPU setups for parity.
Interconnects amplify this: NVLink on GB300 enables seamless scaling across nodes at high speeds, ideal for cluster-wide inference. PCIe on RTX 5060 suffices for standalone use but bottlenecks large-scale operations, emphasizing GB300 for production AI versus RTX 5060 for prototyping.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
RTX 5060
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vast.ai | 2×NVIDIA GeForce RTX 5060 Ti 16GB VRAM | 16GB | 128 vCPU 63GB RAM 1345GB Storage | Maryland | $0.27/GPU/hr $0.53/hr total (2×) | Available |
When to Choose the GB300
The GB300 excels in enterprise-scale AI deployments requiring extreme capacity. With 288 GB HBM3e VRAM and 12000 GB/s bandwidth, it handles full-parameter training of trillion-scale LLMs without model parallelism. Its 2250 TFLOPS FP16 and 4500 TFLOPS FP8 suit high-throughput inference serving.
Datacenter users prioritize GB300 for NVLink-enabled clusters and 1400W TDP tolerance in rack-scale systems.
When to Choose the RTX 5060
The RTX 5060 fits budget-conscious users needing accessible compute. Priced from $0.07 per hour with an average of $0.15 per hour across six providers, it offers 23.1 TFLOPS FP16/FP32 in a 180W PCIe package for desktops or light cloud instances.
Prosumer workflows like gaming, video editing, or small-scale inference benefit from its 12 GB GDDR7 VRAM without datacenter overhead.
Use Cases
GB300's 288 GB HBM3e VRAM fits massive models without sharding. Its 2250 TFLOPS FP16 accelerates convergence on large datasets.
4500 TFLOPS FP8 on GB300 delivers high-throughput serving for production. 12000 GB/s bandwidth supports large batch sizes.
288 GB VRAM handles full fine-tuning of billion-parameter models. NVLink enables efficient multi-GPU scaling.
RTX 5060's 12 GB GDDR7 and 23.1 TFLOPS FP16 suffice for image generation at $0.07 per hour. Low 180W TDP fits consumer setups.
GB300's 90 TFLOPS FP32 and high bandwidth excel in simulations. 288 GB VRAM manages complex datasets.
Frequently Asked Questions
What is the VRAM difference between GB300 and RTX 5060?▾
GB300 provides 288 GB HBM3e, enabling large model hosting. RTX 5060 offers 12 GB GDDR7, suitable for smaller workloads. This 24x gap affects maximum batch sizes and model scales.
How do FP16 performances compare?▾
GB300 achieves 2250 TFLOPS FP16 for rapid AI training. RTX 5060 delivers 23.1 TFLOPS, nearly 100x less. The delta favors GB300 in mixed-precision compute.
What are the power requirements?▾
GB300 demands 1400W TDP for datacenter power supplies. RTX 5060 uses 180W, compatible with standard desktops. This influences deployment costs and cooling.
Is RTX 5060 available for cloud rental?▾
RTX 5060 starts at $0.07 per hour, averaging $0.15 per hour across six providers. GB300 has no live offers currently. Pricing makes RTX 5060 immediately accessible.
Which has higher memory bandwidth?▾
GB300's 12000 GB/s dwarfs RTX 5060's 448 GB/s by over 26x. Higher bandwidth on GB300 boosts data throughput for large batches. RTX 5060 suffices for lighter tasks.
What form factors do they use?▾
GB300 uses SXM with NVSwitch and NVLink for clusters. RTX 5060 employs PCIe for single-GPU systems. This suits GB300 for scaled AI, RTX 5060 for standalone use.
Which is cheaper to rent, the GB300 or the RTX 5060?▾
Cloud rental prices for both the GB300 and RTX 5060 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 5060?▾
The GB300 has 288 GB of HBM3e memory. The RTX 5060 has 12 GB of GDDR7 memory.
Can I find GB300 and RTX 5060 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 5060?▾
The GB300 uses the Blackwell Ultra architecture (2025) while the RTX 5060 uses Blackwell (2025). The GB300 delivers 97.4x the FP16 throughput and 26.8x the memory bandwidth of the RTX 5060.