GB300 SXM6 vs RTX 3080 Ti

Blackwell UltravsAmpereUpdated 35 days ago

The NVIDIA GB300 SXM6 dominates for AI and HPC workloads: 2250 TFLOPS FP16 and 288 GB VRAM enable training massive LLMs infeasible on the RTX 3080 Ti's 29.8 TFLOPS and 12 GB. For most cloud GPU users focused on machine learning, the GB300 SXM6 is the clear winner despite higher power and unavailability.

Specifications Compared

SpecGB300RTX-3080
TDP1400W320W
VRAM288 GB10-12 GB
Memory TypeHBM3eGDDR6X
ArchitectureBlackwell UltraAmpere
Form FactorsSXMPCIe
InterconnectNVSwitch, NVLink
FP8 Performance4,500 TFLOPS
FP16 Performance2,250 TFLOPS29.8 TFLOPS
FP32 Performance90 TFLOPS29.8 TFLOPS
FP64 Performance45 TFLOPS
INT8 Performance4,500 TOPS
Memory Bandwidth12,000 GB/s760 GB/s

Performance Analysis

Compute throughput defines workload suitability: the GB300 SXM6 delivers 2250 TFLOPS FP16 and 4500 TFLOPS FP8, enabling rapid AI training and inference on models with billions of parameters. The RTX 3080 Ti's 29.8 TFLOPS FP16 limits it to smaller models or batch sizes. FP32 performance at 90 TFLOPS on the GB300 SXM6 supports scientific simulations, exceeding the RTX 3080 Ti's 29.8 TFLOPS.

Memory bandwidth profoundly impacts efficiency. The GB300 SXM6's 12000 GB/s sustains large batch sizes in training, reducing overhead in transformer models. The RTX 3080 Ti's 760 GB/s constrains batches, slowing convergence on memory-intensive tasks. VRAM capacity of 288 GB on the GB300 SXM6 fits full precision for LLMs up to hundreds of billions parameters; 12 GB on the RTX 3080 Ti forces quantization or offloading.

Power and form factor influence deployment. The GB300 SXM6's 1400W TDP demands robust cooling in SXM setups, while the RTX 3080 Ti's 320W fits standard PCIe servers, aiding quick prototyping.

Live Cloud Pricing

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When to Choose the GB300 SXM6

Opt for the NVIDIA GB300 SXM6 in large-scale AI training where 288 GB HBM3e VRAM and 12000 GB/s bandwidth handle massive datasets without swapping. Its 2250 TFLOPS FP16 accelerates convergence on models exceeding 100B parameters, ideal for research labs scaling to exaFLOP clusters via NVLink.

Inference at scale benefits from 4500 TFLOPS FP8, serving high-throughput enterprise deployments.

When to Choose the RTX 3080 Ti

Choose the NVIDIA GeForce RTX 3080 Ti for budget-conscious tasks like gaming or small-scale inference, with cloud pricing from $0.08/hr. Its 12 GB GDDR6X and 29.8 TFLOPS FP16 suffice for Stable Diffusion or fine-tuning models under 7B parameters.

PCIe compatibility enables easy integration in personal or small cloud instances, avoiding the GB300 SXM6's 1400W power needs.

Use Cases

LLM Training
GB300 SXM6

The GB300 SXM6's 288 GB VRAM and 2250 TFLOPS FP16 support full-parameter training on models over 100B parameters. The RTX 3080 Ti's 12 GB limits it to tiny models.

LLM Inference
GB300 SXM6

4500 TFLOPS FP8 and 12000 GB/s bandwidth enable high-throughput serving. RTX 3080 Ti struggles with batch sizes beyond small queries.

Fine-tuning
Either

RTX 3080 Ti handles models under 7B at $0.08/hr; GB300 SXM6 excels for larger ones with 90 TFLOPS FP32.

Stable Diffusion
RTX 3080 Ti

RTX 3080 Ti's 29.8 TFLOPS FP16 generates images quickly on 12 GB VRAM. GB300 SXM6 overkill for consumer diffusion.

Scientific Computing
GB300 SXM6

90 TFLOPS FP32 and NVLink scaling tackle simulations; RTX 3080 Ti's 29.8 TFLOPS suits prototypes only.

Frequently Asked Questions

What is the VRAM difference between GB300 SXM6 and RTX 3080 Ti?

The GB300 SXM6 has 288 GB HBM3e VRAM. The RTX 3080 Ti offers 12 GB GDDR6X. This enables the GB300 SXM6 to load massive models without quantization.

How do FP16 performances compare?

GB300 SXM6 achieves 2250 TFLOPS FP16. RTX 3080 Ti reaches 29.8 TFLOPS FP16. The gap favors GB300 SXM6 for AI acceleration by over 75x.

What are the power requirements?

GB300 SXM6 demands 1400W TDP in SXM form. RTX 3080 Ti uses 320W in PCIe. Lower power aids RTX 3080 Ti in edge deployments.

Is there cloud pricing for these GPUs?

No live offers exist for GB300 SXM6. RTX 3080 Ti starts at $0.08/hr, averaging $0.14/hr across 4 providers.

Which has higher memory bandwidth?

GB300 SXM6 provides 12000 GB/s. RTX 3080 Ti offers 760 GB/s. Higher bandwidth on GB300 SXM6 boosts large batch training.

What architectures do they use?

GB300 SXM6 uses Blackwell Ultra from 2025. RTX 3080 Ti employs Ampere from 2020. Newer architecture delivers FP8 at 4500 TFLOPS on GB300 SXM6.

Which is cheaper to rent, the GB300 or the RTX 3080?

Cloud rental prices for both the GB300 and RTX 3080 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 3080?

The GB300 has 288 GB of HBM3e memory. The RTX 3080 has 10 to 12 GB of GDDR6X memory.

Can I find GB300 and RTX 3080 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 3080?

The GB300 uses the Blackwell Ultra architecture (2025) while the RTX 3080 uses Ampere (2020). The GB300 delivers 75.5x the FP16 throughput and 15.8x the memory bandwidth of the RTX 3080.