Blackwell Ultra B300 vs Hopper H100 SXM5
Complete side-by-side comparison of specs, performance, memory, power efficiency, and pricing.
Blackwell Ultra B300
100
Spec Wins
Hopper H100 SXM5
73
Detailed Specifications
Blackwell Ultra B300 — Best For
Hopper H100 SXM5 — Best For
Who Should Choose Each GPU?
Choose Blackwell Ultra B300 if you…
- ✓Need maximum CUDA/TensorRT/vLLM ecosystem compatibility
- ✓Need more VRAM (288GB vs 80GB) for large model inference
- ✓Prioritize raw FP8 throughput (7,000 vs 3,958 TFLOPS)
- ✓Running Trillion-Parameter Training workloads
- ✓Running AGI Research workloads
- ✓Running Sovereign AI workloads
Choose Hopper H100 SXM5 if you…
- ✓Need maximum CUDA/TensorRT/vLLM ecosystem compatibility
- ✓Have power-constrained data centers (700W vs 1400W TDP)
- ✓Working with a tighter CapEx budget (lower list price)
- ✓Running LLM Training workloads
- ✓Running HPC workloads
Verdict
The Blackwell Ultra B300 and Hopper H100 SXM5 target different priorities. The Blackwell Ultra B300's 288GB of HBM3e gives it a clear edge for large-model inference where fitting the full model in VRAM eliminates quantization overhead. For training throughput, the Blackwell Ultra B300's 7,000 FP8 TFLOPS outpaces the Hopper H100 SXM5's 3,958 TFLOPS. Both GPUs use CUDA, so ecosystem switching cost is not a factor. Use our TCO Calculator to model the full 3-year cost difference for your specific utilization and power costs.
Blackwell Ultra B300 vs Hopper H100 SXM5: Common Questions
Which is faster, Blackwell Ultra B300 or Hopper H100 SXM5?+
In FP8 throughput, the Blackwell Ultra B300 leads with 7,000 TFLOPS vs 3,958 TFLOPS. For LLM inference, memory capacity and bandwidth often matter more than raw TFLOPS — the Blackwell Ultra B300 has more VRAM (288GB).
Is Blackwell Ultra B300 or Hopper H100 SXM5 better for LLM training?+
For LLM training at scale, the Blackwell Ultra B300 has higher raw throughput. However, the choice also depends on your software stack: Blackwell Ultra B300 offers CUDA compatibility with the widest framework support (PyTorch, JAX, TensorRT).
What is the price difference between Blackwell Ultra B300 and Hopper H100 SXM5?+
The Blackwell Ultra B300 is estimated at $40,000 per unit and the Hopper H100 SXM5 at $25,000. Actual pricing varies by vendor, volume, and configuration. Check our Buy page for current reseller pricing.
Which GPU is more power efficient, Blackwell Ultra B300 or Hopper H100 SXM5?+
The Hopper H100 SXM5 has a lower TDP (700W vs 1400W). Performance-per-watt depends on your workload — for FP8 inference, divide TFLOPS by TDP: Blackwell Ultra B300 = 5.0 TFLOPS/W vs Hopper H100 SXM5 = 5.7 TFLOPS/W.