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Tesla V100 SXM2 32GB vs Hopper H100 SXM5

Complete side-by-side comparison of specs, performance, memory, power efficiency, and pricing.

NVIDIA

Tesla V100 SXM2 32GB

9

Spec Wins

NVIDIA

Hopper H100 SXM5

73

Detailed Specifications

SpecTesla V100 SXM2 32GBHopper H100 SXM5
ArchitectureVolta (GV100) Hopper
Memory32GB HBM2 80GB HBM3
Memory Bandwidth900 GB/s 3,350 GB/s
FP16 TFLOPS125 1,979
FP8 TFLOPS0 3,958
BF16 TFLOPS0 1,979
INT8 TOPS62 3,958
TDP300W 700W
InterconnectNVLink 2.0 (300 GB/s) (300 GB/s) NVLink 4.0 (900 GB/s) (900 GB/s)
Perf Score9 73
EcosystemCUDA CUDA
Est. Price$3,000 $25,000

Tesla V100 SXM2 32GB — Best For

Budget ML TrainingClassic Deep LearningLegacy Pipelines

Hopper H100 SXM5 — Best For

LLM TrainingHPC

Who Should Choose Each GPU?

Choose Tesla V100 SXM2 32GB if you…

  • Need maximum CUDA/TensorRT/vLLM ecosystem compatibility
  • Have power-constrained data centers (300W vs 700W TDP)
  • Working with a tighter CapEx budget (lower list price)
  • Running Budget ML Training workloads
  • Running Classic Deep Learning workloads
  • Running Legacy Pipelines workloads

Choose Hopper H100 SXM5 if you…

  • Need maximum CUDA/TensorRT/vLLM ecosystem compatibility
  • Need more VRAM (80GB vs 32GB) for large model inference
  • Prioritize raw FP8 throughput (3,958 vs 0 TFLOPS)
  • Running LLM Training workloads
  • Running HPC workloads

Verdict

The Tesla V100 SXM2 32GB and Hopper H100 SXM5 target different priorities. The Hopper H100 SXM5's 80GB of HBM3 gives it a clear edge for large-model inference where fitting the full model in VRAM eliminates quantization overhead. For training throughput, the Hopper H100 SXM5's 3,958 FP8 TFLOPS outpaces the Tesla V100 SXM2 32GB's 0 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.

Tesla V100 SXM2 32GB vs Hopper H100 SXM5: Common Questions

Which is faster, Tesla V100 SXM2 32GB or Hopper H100 SXM5?+

In FP8 throughput, the Hopper H100 SXM5 leads with 3,958 TFLOPS vs 0 TFLOPS. For LLM inference, memory capacity and bandwidth often matter more than raw TFLOPS — the Hopper H100 SXM5 has more VRAM (80GB).

Is Tesla V100 SXM2 32GB or Hopper H100 SXM5 better for LLM training?+

For LLM training at scale, the Hopper H100 SXM5 has higher raw throughput. However, the choice also depends on your software stack: Tesla V100 SXM2 32GB offers CUDA compatibility with the widest framework support (PyTorch, JAX, TensorRT).

What is the price difference between Tesla V100 SXM2 32GB and Hopper H100 SXM5?+

The Tesla V100 SXM2 32GB is estimated at $3,000 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, Tesla V100 SXM2 32GB or Hopper H100 SXM5?+

The Tesla V100 SXM2 32GB has a lower TDP (300W vs 700W). Performance-per-watt depends on your workload — for FP8 inference, divide TFLOPS by TDP: Tesla V100 SXM2 32GB = 0.0 TFLOPS/W vs Hopper H100 SXM5 = 5.7 TFLOPS/W.

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