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FAQ
Q: Should new deployments choose B200 or H200? B200 achieves lower cost-per-inference for most workloads. New deployments benefit from B200 unless already committed to H200-compatible infrastructure.
Q: Is B200 production-ready as of March 2026? Yes. RunPod and several specialized providers offer B200 with stable performance. Ecosystem maturity lags H200 but reaches acceptable production standards.
Q: How much faster is B200 than H100? B200 achieves 2-3x throughput improvement for inference. Latency improvements reach 50-70%. Cost-per-inference typically halves despite 2-2.2x hourly pricing.
Q: Can teams migrate from H100 to B200 easily? CUDA code requires no changes. vLLM and other frameworks support B200 natively. Migration mainly involves changing instance type, requiring minimal application changes.
Q: What's the B200 price versus older generations? H100: $2.69/hour. H200: $3.59/hour. B200: $5.98/hour on RunPod. The cost-per-inference gap narrows despite hourly premium.
Related Resources
Sources
- NVIDIA: H200 and B200 official specifications and performance data (as of March 2026)
- RunPod: GPU pricing and infrastructure documentation
- Lambda Labs: H200/B200 availability and benchmarks
- Hugging Face: Transformer inference benchmarks
- Real-world production deployment reports
- Industry analysis of GPU generational improvements