GB300 SXM6 vs MI325X

Blackwell UltravsCDNA 3Updated 35 days ago

NVIDIA GB300 emerges as the superior choice for dominant AI workloads like LLM training and inference. Its 2250 TFLOPS FP16, 4500 TFLOPS FP8, 288 GB VRAM, and 12000 GB/s bandwidth outperform MI325X equivalents, enabling faster model scaling despite higher 1400W TDP.

Specifications Compared

SpecGB300MI325X
TDP1400W750W
VRAM288 GB256 GB
Memory TypeHBM3eHBM3e
ArchitectureBlackwell UltraCDNA 3
Form FactorsSXMOAM
InterconnectNVSwitch, NVLinkInfinity Fabric
FP8 Performance4,500 TFLOPS2,614 TFLOPS
FP16 Performance2,250 TFLOPS1,307 TFLOPS
FP32 Performance90 TFLOPS1307 TFLOPS
FP64 Performance45 TFLOPS40.9 TFLOPS
INT8 Performance4,500 TOPS2,614 TOPS
Memory Bandwidth12,000 GB/s6,000 GB/s

Performance Analysis

NVIDIA GB300 excels in low-precision compute critical for AI training and inference: its 2250 TFLOPS FP16 rate doubles MI325X's 1307 TFLOPS, enabling faster matrix multiplications in transformer models. FP8 performance reaches 4500 TFLOPS on GB300 against 2614 TFLOPS on MI325X, ideal for quantized inference. However, MI325X maintains parity in FP32 at 1307 TFLOPS while GB300 drops to 90 TFLOPS, benefiting simulations requiring higher precision. This FP16/FP32 delta means GB300 prioritizes scale-out training over general-purpose floating point tasks. Memory bandwidth impacts batch sizes directly: GB300's 12000 GB/s supports larger batches in memory-bound workloads like LLM fine-tuning, reducing iteration times compared to MI325X's 6000 GB/s. Higher VRAM on GB300, 288 GB versus 256 GB, accommodates bigger models without partitioning.

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When to Choose the GB300 SXM6

NVIDIA GB300 suits hyperscale AI training clusters needing maximum throughput. Its 2250 TFLOPS FP16 and 12000 GB/s bandwidth handle massive datasets efficiently, as in training models exceeding 1 trillion parameters. SXM form factor with NVLink enables seamless multi-GPU scaling for exascale systems. Deploy GB300 where power density supports 1400W TDP per card.

When to Choose the MI325X

AMD Instinct MI325X fits power-constrained environments or FP32-heavy workloads. At 750W TDP, it consumes half the power of GB300 while delivering 1307 TFLOPS FP32, suitable for scientific simulations or HPC tasks. OAM form factor and Infinity Fabric support dense rack integration without excessive cooling demands.

Use Cases

LLM Training
GB300 SXM6

GB300 provides 2250 TFLOPS FP16 and 12000 GB/s bandwidth, doubling MI325X capabilities for faster large-scale training. Higher 288 GB VRAM supports unpartitioned trillion-parameter models.

LLM Inference
GB300 SXM6

GB300's 4500 TFLOPS FP8 excels in quantized serving, paired with 12000 GB/s bandwidth for high-throughput requests. It handles larger batch sizes than MI325X's 2614 TFLOPS FP8.

Fine-tuning
GB300 SXM6

288 GB VRAM and superior FP16 performance on GB300 fit memory-intensive fine-tuning without model sharding. Bandwidth advantage reduces epoch times over MI325X.

Stable Diffusion
Either

Both offer ample HBM3e VRAM for diffusion models, but GB300 accelerates low-precision generation while MI325X suffices for smaller-scale inference at lower power.

Scientific Computing
MI325X

MI325X delivers 1307 TFLOPS FP32, matching its FP16 rate for balanced HPC simulations, unlike GB300's 90 TFLOPS FP32. Lower 750W TDP aids dense deployments.

Frequently Asked Questions

Which has more VRAM, GB300 or MI325X?

NVIDIA GB300 offers 288 GB HBM3e VRAM, exceeding AMD MI325X's 256 GB. This difference supports larger models on GB300 without data parallelism. Both use HBM3e for high-speed access.

How do FP16 performances compare?

GB300 achieves 2250 TFLOPS FP16, nearly double MI325X's 1307 TFLOPS. GB300 suits AI training acceleration. MI325X balances with equal FP32 performance.

What are the TDPs of these GPUs?

GB300 requires 1400W TDP, while MI325X uses 750W. MI325X enables more cards per rack under power limits. GB300 demands advanced cooling.

Which has higher memory bandwidth?

GB300 provides 12000 GB/s, twice MI325X's 6000 GB/s. Higher bandwidth on GB300 boosts batch sizes in memory-bound tasks. This aids LLM workloads significantly.

What interconnects do they use?

GB300 employs NVSwitch and NVLink for low-latency scaling. MI325X uses Infinity Fabric for cluster connectivity. Choices depend on ecosystem preferences.

Are there live pricing offers?

No live offers exist for either GPU currently. Both represent upcoming data center options without spot market availability. Monitor gpuperhour.com for updates.

Which is cheaper to rent, the GB300 or the MI325X?

Cloud rental prices for both the GB300 and MI325X 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 MI325X?

The GB300 has 288 GB of HBM3e memory. The MI325X has 256 GB of HBM3e memory.

Can I find GB300 and MI325X 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 MI325X?

The GB300 uses the Blackwell Ultra architecture (2025) while the MI325X uses CDNA 3 (2024). The GB300 delivers 1.7x the FP16 throughput and 2.0x the memory bandwidth of the MI325X.