Specifications Compared
| Spec | GB300 | MI250X |
|---|---|---|
| TDP | 1400W | 560W |
| VRAM | 288 GB | 128 GB |
| Memory Type | HBM3e | HBM2e |
| Architecture | Blackwell Ultra | CDNA 2 |
| Form Factors | SXM | OAM |
| Interconnect | NVSwitch, NVLink | Infinity Fabric |
| FP8 Performance | 4,500 TFLOPS | |
| FP16 Performance | 2,250 TFLOPS | 383 TFLOPS |
| FP32 Performance | 90 TFLOPS | 383 TFLOPS |
| FP64 Performance | 45 TFLOPS | 48 TFLOPS |
| INT8 Performance | 4,500 TOPS | |
| Memory Bandwidth | 12,000 GB/s | 3,277 GB/s |
Performance Analysis
Memory specifications define key real-world advantages for the GB300. Its 288 GB HBM3e capacity supports larger models and batch sizes than the MI250X's 128 GB HBM2e, enabling training of massive language models without excessive multi-GPU scaling. Bandwidth at 12000 GB/s on GB300 minimizes data bottlenecks during memory-intensive operations, compared to 3277 GB/s on MI250X, which limits throughput for high-batch scenarios.
FP16 performance at 2250 TFLOPS on GB300 accelerates AI training and inference far beyond MI250X's 383 TFLOPS, reducing epoch times significantly for deep learning workloads. The FP32 rating of 90 TFLOPS on GB300 lags behind MI250X's balanced 383 TFLOPS, potentially favoring MI250X in precision-sensitive simulations. GB300's FP8 capability of 4500 TFLOPS optimizes low-precision inference, ideal for deployment at scale.
Power efficiency varies: MI250X's 560W TDP suits dense clusters, while GB300's 1400W demands robust cooling. Overall, GB300 excels in memory-bound and high-throughput AI tasks, interpreting specs into faster iteration cycles.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
MI250X
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Cirrascale | 4×AMD Instinct MI250X 128GB VRAM | 128GB | 256 vCPU 1024GB RAM 11882GB Storage | United States | $1.28/GPU/hr $5.12/hr total (4×) | |||
Cirrascale | 4×AMD Instinct MI250X 128GB VRAM | 128GB | 256 vCPU 1024GB RAM 11882GB Storage | United States | $1.44/GPU/hr $5.76/hr total (4×) | |||
Cirrascale | 4×AMD Instinct MI250X 128GB VRAM | 128GB | 256 vCPU 1024GB RAM 11882GB Storage | United States | $1.52/GPU/hr $6.08/hr total (4×) | |||
Cirrascale | 4×AMD Instinct MI250X 128GB VRAM | 128GB | 256 vCPU 1024GB RAM 11882GB Storage | United States | $1.60/GPU/hr $6.40/hr total (4×) |
When to Choose the GB300
The GB300 suits scenarios demanding extreme scale, such as training foundation models exceeding 100 billion parameters. Its 288 GB VRAM and 12000 GB/s bandwidth handle massive datasets without fragmentation, outperforming MI250X's 128 GB and 3277 GB/s limits. FP16 at 2250 TFLOPS and FP8 at 4500 TFLOPS enable rapid prototyping for inference-heavy applications.
Researchers prioritizing future-proofing select GB300 for its NVSwitch and NVLink interconnects, facilitating seamless multi-node scaling unavailable on MI250X.
When to Choose the MI250X
The MI250X fits budget-conscious deployments requiring immediate access. Cloud pricing starts at $1.28 per hour with an average of $1.46 per hour across four providers, contrasting GB300's lack of live offers. Its 560W TDP supports efficient, power-sensitive environments over GB300's 1400W draw.
Balanced FP16 and FP32 at 383 TFLOPS each make MI250X preferable for scientific computing or mixed-precision workloads where GB300's FP32 of 90 TFLOPS underperforms.
Use Cases
GB300's 288 GB VRAM and 2250 TFLOPS FP16 support massive models and large batches, far exceeding MI250X's 128 GB and 383 TFLOPS.
FP8 performance at 4500 TFLOPS on GB300 optimizes high-volume serving, with 12000 GB/s bandwidth enabling larger contexts than MI250X's 3277 GB/s.
288 GB HBM3e capacity on GB300 accommodates full model fine-tuning without sharding, unlike MI250X's 128 GB constraint.
MI250X's balanced 383 TFLOPS FP16/FP32 suffices for image generation at lower cost from $1.28/hr; GB300 overkill unless scaling to ultra-high resolutions.
MI250X's equal 383 TFLOPS FP16/FP32 excels in precision simulations; lower 560W TDP aids dense HPC clusters over GB300's imbalanced specs.
Frequently Asked Questions
Which GPU has more VRAM?▾
The GB300 provides 288 GB HBM3e, doubling MI250X's 128 GB HBM2e. This enables handling larger AI models on GB300 without multi-GPU setups.
What is the FP16 performance comparison?▾
GB300 delivers 2250 TFLOPS FP16, nearly six times MI250X's 383 TFLOPS. This gap accelerates deep learning training significantly on GB300.
Is GB300 available for cloud rental now?▾
No live offers exist for GB300 currently. MI250X is available from $1.28 per hour, averaging $1.46 per hour across four providers.
How do power requirements differ?▾
GB300 requires 1400W TDP, over twice MI250X's 560W. MI250X suits power-efficient deployments better.
Which has higher memory bandwidth?▾
GB300 achieves 12000 GB/s, exceeding MI250X's 3277 GB/s by over 3.6 times. Higher bandwidth on GB300 reduces bottlenecks in data-heavy tasks.
What interconnects do they use?▾
GB300 employs NVSwitch and NVLink for multi-GPU scaling. MI250X uses Infinity Fabric, suitable for AMD ecosystems.
Which is cheaper to rent, the GB300 or the MI250X?▾
Cloud rental prices for both the GB300 and MI250X 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 MI250X?▾
The GB300 has 288 GB of HBM3e memory. The MI250X has 128 GB of HBM2e memory.
Can I find GB300 and MI250X 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 MI250X?▾
The GB300 uses the Blackwell Ultra architecture (2025) while the MI250X uses CDNA 2 (2021). The GB300 delivers 5.9x the FP16 throughput and 3.7x the memory bandwidth of the MI250X.