Specifications Compared
| Spec | B200 | GB300 |
|---|---|---|
| TDP | 1000W | 1400W |
| VRAM | 192 GB | 288 GB |
| CUDA Cores | 18,432 | |
| Memory Type | HBM3e | HBM3e |
| Architecture | Blackwell | Blackwell Ultra |
| Form Factors | SXM, NVL | SXM |
| Interconnect | NVLink, PCIe 6.0, InfiniBand | NVSwitch, NVLink |
| Tensor Cores | 576 | |
| FP8 Performance | 9,000 TFLOPS | 4,500 TFLOPS |
| FP16 Performance | 4,500 TFLOPS | 2,250 TFLOPS |
| FP32 Performance | 90 TFLOPS | 90 TFLOPS |
| FP64 Performance | 45 TFLOPS | 45 TFLOPS |
| INT8 Performance | 9,000 TOPS | 4,500 TOPS |
| Memory Bandwidth | 8,000 GB/s | 12,000 GB/s |
Performance Analysis
The B200 SXM outperforms in low-precision compute, with 4500 TFLOPS FP16 compared to the GB300 SXM6's 2250 TFLOPS, accelerating neural network training where FP16 dominates. This delta enables faster convergence in large language model training cycles. Both GPUs match at 90 TFLOPS FP32, ensuring parity for precision-sensitive tasks like physics simulations.
FP8 performance favors B200 SXM at 9000 TFLOPS over 4500 TFLOPS, benefiting quantized inference for serving models at scale with reduced latency. However, GB300 SXM6's 288 GB VRAM and 12000 GB/s bandwidth, versus 192 GB and 8000 GB/s, allow larger batch sizes in memory-intensive workloads, minimizing data transfer bottlenecks and improving throughput for massive datasets.
Power consumption differs: B200 SXM's 1000W TDP contrasts with 1400W for GB300 SXM6, impacting cooling and density in racks but enabling sustained peak performance in expansive clusters.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
B200 SXM
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Nebius | NVIDIA B200 SXM 192GB VRAM | 192GB | 20 vCPU 224GB RAM | 🌍Europe | $3.95/GPU/hr | |||
 Cirrascale | 8×NVIDIA B200 SXM 192GB VRAM | 192GB | 192 vCPU 2048GB RAM 43923GB Storage | United States | $4.79/GPU/hr $38.32/hr total (8×) | |||
Cirrascale | 8×NVIDIA B200 SXM 192GB VRAM | 192GB | 192 vCPU 2048GB RAM 43923GB Storage | United States | $5.39/GPU/hr $43.12/hr total (8×) | |||
Cirrascale | 8×NVIDIA B200 SXM 192GB VRAM | 192GB | 192 vCPU 2048GB RAM 43923GB Storage | United States | $5.69/GPU/hr $45.52/hr total (8×) | |||
 RunPod | NVIDIA B200 SXM 192GB VRAM | 192GB | 28 vCPU 283GB RAM | California | $5.89/GPU/hr |
When to Choose the B200 SXM
The B200 SXM is the optimal choice for projects requiring immediate deployment and superior low-precision throughput. Its 4500 TFLOPS FP16 and 9000 TFLOPS FP8 outperform GB300 SXM6 equivalents, paired with cloud pricing from $1.71 per hour. Lower 1000W TDP suits power-constrained environments for rapid LLM training or inference prototyping.
When to Choose the GB300 SXM6
Select the GB300 SXM6 for memory-bound applications leveraging its 288 GB HBM3e VRAM and 12000 GB/s bandwidth, which support enormous models without partitioning. This configuration excels in large-batch training or inference of frontier-scale LLMs, where B200 SXM's 192 GB limits scalability.
Use Cases
B200 SXM's 4500 TFLOPS FP16 exceeds GB300 SXM6's 2250 TFLOPS, speeding up training iterations. Availability and pricing from $1.71 per hour enable quick starts.
Superior 9000 TFLOPS FP8 on B200 SXM doubles GB300 SXM6's 4500 TFLOPS for quantized serving. Lower latency suits production deployments.
Both offer 90 TFLOPS FP32 for precision needs, with B200 SXM available now and GB300 SXM6 providing more 288 GB VRAM for larger adapters.
GB300 SXM6's 288 GB VRAM and 12000 GB/s bandwidth handle high-resolution image generation batches better than B200 SXM's 192 GB.
Identical 90 TFLOPS FP32 performance serves simulations equally. Choose B200 SXM for current access or GB300 SXM6 for memory-intensive datasets.
Frequently Asked Questions
What is the VRAM difference between B200 SXM and GB300 SXM6?▾
The GB300 SXM6 provides 288 GB HBM3e VRAM, compared to 192 GB on B200 SXM. This enables GB300 SXM6 to manage larger models without multi-GPU setups. Bandwidth follows suit at 12000 GB/s versus 8000 GB/s.
Which has higher FP16 performance?▾
B200 SXM achieves 4500 TFLOPS FP16, doubling GB300 SXM6's 2250 TFLOPS. This benefits training workloads heavily reliant on FP16 precision. FP8 follows with 9000 TFLOPS on B200 SXM over 4500 TFLOPS.
What are the cloud prices for these GPUs?▾
B200 SXM pricing starts at $1.71 per hour, averaging $4.60 per hour across 13 offers. GB300 SXM6 has no live cloud offers available yet. Prices reflect 2024 market data.
How do TDPs compare?▾
B200 SXM consumes 1000W TDP, lower than GB300 SXM6's 1400W. This makes B200 SXM easier for cooling in dense racks. Higher TDP on GB300 SXM6 supports peak sustained loads.
When is GB300 SXM6 available?▾
GB300 SXM6 targets 2025 release as Blackwell Ultra. No live cloud instances exist currently. B200 SXM is deployable now with 13 offers.
Do they share the same FP32 performance?▾
Yes, both deliver 90 TFLOPS FP32. This parity suits scientific computing or legacy codes needing full precision. Differences lie in lower-precision metrics.
Which is cheaper to rent, the B200 or the GB300?▾
Cloud rental prices for both the B200 and GB300 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 B200 have compared to the GB300?▾
The B200 has 192 GB of HBM3e memory. The GB300 has 288 GB of HBM3e memory.
Can I find B200 and GB300 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 B200 and the GB300?▾
The B200 uses the Blackwell architecture (2024) while the GB300 uses Blackwell Ultra (2025). The B200 delivers 2.0x the FP16 throughput and 1.5x the memory bandwidth of the GB300.