---
type: Comparison
title: NVIDIA Blackwell (B200) vs NVIDIA Hopper (H100)
description: NVIDIA Blackwell (B200) vs NVIDIA Hopper (H100)
resource: "https://www.contextstudios.ai/comparisons/blackwell-vs-hopper"
category: technology
language: en
timestamp: "2026-03-18T10:07:34.065Z"
---

# NVIDIA Blackwell (B200) vs NVIDIA Hopper (H100)

## Comparison Factors

| Factor | NVIDIA Blackwell (B200) | NVIDIA Hopper (H100) | Winner |
|--------|------|------|--------|
| Inference Performance | 30x higher inference throughput via FP4, 192GB HBM3e, and NVLink Switch. Holds 1T-parameter models entirely in VRAM. | Good inference performance in FP8 and FP16. Production deployment standard 2023-2025. Proven and broadly available. | a |
| Training Performance | 2-4x better than H100 for modern architectures via second-gen Transformer Engine. | Market standard for LLM training 2022-2025. Well-suited for models up to 70B parameters on single node. | a |
| Energy Efficiency | Significantly more efficient: FP4 enables 4x more operations per watt. | Good efficiency for its generation, but significantly less efficient than Blackwell. | a |
| Price and Availability | More expensive (B200: >$30k), limited availability in 2025. Long-term cheaper through efficiency gains. | Lower spot-market prices due to larger supply. H100: $25-28k, broad cloud availability. | b |
| FP4 Support | Native FP4 at hardware level. Enables 2x more efficiency than FP8 without quality loss. | No native FP4. FP8 as lowest precision tier. INT4 possible but with latency overhead. | a |
| Memory Capacity | 192GB HBM3e per B200 chip. GB200 NVL72 = 1.4TB total. Enables 400B+ parameter models without model parallelism. | 80GB HBM3 per H100. DGX H100 = 640GB total. Sufficient for models up to ~70B without parallelism. | a |

## Key Statistics

- NVIDIA B200 achieves 20 petaflops FP4 inference performance vs 4 petaflops FP8 on H100 - 5x improvement
- GB200 NVL72 can hold a 1-trillion-parameter model entirely in VRAM - first time possible without model parallelism
- H100 remains the dominant inference chip in cloud market with 60%+ market share at major cloud providers in 2025
- Forecast: Blackwell-based cloud instances will be 50% cheaper than equivalent H100 instances by end 2026

Keywords: NVIDIA Blackwell vs Hopper, B200 vs H100, GPU comparison, AI chip comparison, NVIDIA GTC 2024