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H100 vs H200 vs B200: Which GPU Should You Choose?

Wollnut Labs TeamMarch 18, 20255 min

The GPU Landscape in 2025

NVIDIA's datacenter GPU lineup has expanded significantly. Let's break down the three GPUs available on Wollnut Labs and when to use each.

NVIDIA H100 (80GB SXM)

The H100 remains the workhorse of AI infrastructure. With 80GB of HBM3 memory and strong FP8 performance, it handles most ML workloads effectively.

Best for:

  • Fine-tuning models up to 70B parameters (with LoRA/QLoRA)
  • Running inference for most open-source models
  • Distributed training when using 4x or 8x configurations
  • Teams with moderate budgets who need reliable performance

    • Pricing on Wollnut Labs: $2.25/hr per GPU

    NVIDIA H200 (141GB SXM)

    The H200 is the H100's successor with nearly double the memory (141GB HBM3e). This extra memory is transformational for large model work.

    Best for:

  • Fine-tuning 70B+ models with larger batch sizes
  • Running inference on 70B models without quantization
  • Multi-modal model training that requires large context
  • Workloads bottlenecked by memory, not compute

    • Pricing on Wollnut Labs: $2.75/hr per GPU

    NVIDIA B200 (192GB HBM3e)

    The B200 is NVIDIA's flagship Blackwell architecture GPU. With 192GB of memory and next-gen compute capabilities, it's built for frontier model work.

    Best for:

  • Training frontier models from scratch
  • Running the largest open-source models at full precision
  • Research pushing the boundaries of model scale
  • Teams that need the absolute best hardware available

    • Pricing on Wollnut Labs: $5.90/hr per GPU

    Quick Decision Guide

    WorkloadRecommended GPU
    Fine-tune 7B-13B modelH100 1x
    Fine-tune 70B model (LoRA)H100 2x or H200 1x
    Run DeepSeek R1 inferenceH100 8x or H200 4x
    Train custom model from scratchH200 8x or B200
    Image generation (SDXL/Flux)H100 1x
    Whisper transcriptionH100 1x

    The Bottom Line

    Start with an H100 for most workloads. Move to H200 when you need more memory. Use B200 for frontier-scale work. With per-minute billing, you can experiment freely without commitment.

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