H100 SXM5
FP8 native, air-cooled, 700W, proven at scale
B200 Blackwell
FP4 native, liquid-cooled, 1000W, NVLink 5.0 (1.8 TB/s)
Head-to-Head Hardware Specs
Side-by-side hardware architecture comparison for H100 SXM5 vs B200 Blackwell.
H100 SXM5
B200 Blackwell
Which GPU Fits Your Workload?
Pre-Training
B200 — FP4 halves memory, doubles throughput for MoE training
Fine-Tuning
H100 — air-cooled, available today, FP8 native
Inference
B200 — 4,500 FP4 TFLOPS delivers 2x tokens/dollar at scale
NVIDIA H100 Hopper vs B200 Blackwell: FP4 Throughput & Liquid-Cooled Infrastructure
Generational architectural duel: 2nd Gen Transformer Engine, NVLink 5 (1.8 TB/s), native FP4 precision, and power density requirements.
Technical Scorecard
Side-by-side infrastructure specs using live pricing data for B200-class hardware.
| Metric | H100 SXM5 | B200 Blackwell |
|---|---|---|
| Network Fabric | NVLink 4.0 (900 GB/s) | NVLink 5.0 (1.8 TB/s) |
| Storage Throughput | Local NVMe (7,000 MB/s) | Local NVMe (12,000 MB/s) |
| Egress Pricing | Provider dependent | Provider dependent |
| SLA Guarantee | 99.9% | 99.9% |
| 8-GPU 100h Cost | $1,512 (8× H100 @ $1.89/hr) | $2,792 (8× B200 @ $3.49/hr) |
Live Pricing Comparison
Spot and reserved rates refreshed from provider APIs. Filtered to B200-class hardware.
| Provider | GPU & VRAM | Interconnect | Spot Rate | On-Demand | Monthly | Status | Action | |
|---|---|---|---|---|---|---|---|---|
Community | NVLink 5.0 (1.8 TB/s) | $3.99 / hr | $9.98 / hr | $2,442 / mo | Instant | |||
Bare Metal | NVLink 5.0 (1.8 TB/s) | $4.49 / hr | $11.23 / hr | $2,748 / mo | Instant | |||
Dedicated | NVLink 5.0 (1.8 TB/s) | $5.49 / hr | $13.73 / hr | $3,360 / mo | Instant | |||
Cloud | NVLink 5.0 (1.8 TB/s) | $5.99 / hr | $14.98 / hr | $3,666 / mo | Instant |
When to Choose H100 SXM5
- Production workloads requiring air-cooled infrastructure
- Teams needing immediate GPU availability
- FP8 workloads where FP4 quality is unacceptable
When to Choose B200 Blackwell
- Frontier model training requiring FP4 precision
- Liquid-cooled datacenter with 1000W rack support
- Extreme-throughput inference where 2x tokens/second matters
Technical Deep-Dive
FP4 vs FP8 Precision
H100: FP8 at 1,979 TFLOPS. B200: FP4 at 4,500 TFLOPS (2.3x more TFLOPS) and FP8 at 2,250 TFLOPS (+14%). FP4 cuts memory in half: Llama 70B FP4 = 35GB (fits single B200 with 157GB headroom). Quality tradeoff: <5% perplexity degradation on standard benchmarks.
NVLink 5.0 vs 4.0
H100: NVLink 4.0 at 900 GB/s per GPU. B200: NVLink 5.0 at 1.8 TB/s (2x bandwidth). For 8-way tensor parallelism, NVLink 5.0 absorbs all-reduce latency even at batch=256 — the doubled bandwidth eliminates the communication overhead that limits H100 scaling at high batch sizes.
Infrastructure Requirements
H100: 700W TDP, air-cooled compatible, available in standard 19-inch racks. B200: 1000W TDP, liquid-cooled mandatory — direct-to-chip liquid cooling required to sustain thermal envelope. Providers offering B200 must have purpose-built AI datacenter infrastructure.
Final Verdict
The B200 delivers 2x inference throughput via FP4 but requires liquid-cooled infrastructure at 1000W TDP. The H100 is deployment-ready in air-cooled datacenters today.