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RTX Pro 6000 vs H100

Explore a head to head comparison of specifications, performance, and pricing.

RTX Pro 6000

The NVIDIA RTX Pro 6000 delivers high-performance computing capabilities for AI, machine learning, and data science applications.

ManufacturerNVIDIA
GPU Architecture
Average Price$7.34/hr
GPU VRAM96 GB
Cloud Availability7 clouds
System Memory1800 GB
CPU Cores240
Storage30.7 TB

H100

The NVIDIA H100 is a Hopper-based GPU that provides exceptional performance, scalability, and economics for AI, deep learning, and HPC workloads.

ManufacturerNVIDIA
GPU ArchitectureHopper
Average Price$10.12/hr
GPU VRAM80 GB
Cloud Availability13 clouds
System Memory1920 GB
CPU Cores252
Storage31.3 TB

RTX Pro 6000 vs H100: Which Should You Choose?

The RTX Pro 6000 offers 96 GB of VRAM — 1.2× the 80 GB on the H100 — making it better suited for large model workloads that require holding more parameters in GPU memory. On FP16 throughput, the H100 delivers 267.6 TFLOPS versus 126 TFLOPS on the RTX Pro 6000 — 2× faster for mixed-precision training and inference. Memory bandwidth favors the H100 at 0.00 TB/s compared to 0.00 TB/s on the RTX Pro 6000, which directly impacts inference latency for memory-bandwidth-bound models. Architecturally, the RTX Pro 6000 is built on Blackwell while the H100 uses Hopper, reflecting different generational capabilities and optimizations. On Shadeform, the RTX Pro 6000 starts from $1.25/hr versus $1.66/hr for the H100 — 33% more expensive — reflecting the performance premium. The H100 is available across 13 cloud providers on Shadeform compared to 7 for the RTX Pro 6000, giving more options for region and pricing flexibility.

RTX Pro 6000 — Best Use Cases

  • Next-generation LLM pre-training at scale
  • Trillion-parameter model inference
  • Ultra-high-throughput AI workloads
  • Advanced HPC and scientific computing

Choose RTX Pro 6000 when:

  • You need 96 GB+ VRAM for large models or long context windows
  • Cost efficiency is your primary concern
  • Your workload does not require peak FP16 throughput
  • Your preferred provider already has availability

H100 — Best Use Cases

  • Training large language models (7B–405B parameters)
  • High-throughput LLM inference
  • Mixture-of-experts and transformer workloads
  • Distributed multi-GPU training runs

Choose H100 when:

  • 80 GB VRAM is sufficient for your workload
  • Maximum performance justifies the higher cost
  • You are training large models or running high-throughput inference
  • You need flexibility across multiple cloud providers or regions

See how the RTX Pro 6000 & H100 compare

Compare detailed hardware specifications and average pricing for the RTX Pro 6000 and H100.

Compare Hardware Specifications

RTX Pro 6000H100
GPU Type
RTX Pro 6000
H100
VRAM per GPU
96 GB
80 GB
Manufacturer
NVIDIA
NVIDIA
Architecture
Blackwell
Hopper
Interconnect
PCIe Gen5
PCIe Gen5 or SXM5
Memory Bandwidth
1.59 TB/s
3.35 TB/s
FP16 TFLOPS
126.0 TFLOPS (1:1)
267.6 TFLOPS (4:1)
CUDA Cores
24064
16896
Tensor Cores
752 (5th Gen)
528 (4th Gen)
RT Cores
188 (4th Gen)
N/A
Base Clock
1860 MHz
1365 MHz
Boost Clock
2600 MHz
1785 MHz
TDP
400W
350-700W
Process Node
TSMC 4N
TSMC 4N
Data Formats
FP4, FP6, FP8, INT8, BF16, FP16, TF32, FP32
FP8, INT8, BF16, FP16, TF32, FP32, FP64

Compare Average On-Demand Pricing

RTX Pro 6000H100
1 GPU
$1.70 /hr
$2.85 /hr
2 GPUs
$3.30 /hr
$5.19 /hr
4 GPUs
$6.60 /hr
$9.79 /hr
8 GPUs
$14.11 /hr
$19.35 /hr

Frequently Asked Questions: RTX Pro 6000 vs H100

The main differences are VRAM (96 GB vs 80 GB), FP16 throughput (126 vs 267.6 TFLOPS), architecture (Blackwell vs Hopper). The RTX Pro 6000 uses the Blackwell architecture while the H100 is based on Hopper, giving each GPU different generational capabilities.

The H100 is generally better for large language model training due to its higher throughput and 80 GB of VRAM, which allows fitting larger models or larger batch sizes in a single pass. For smaller models or fine-tuning tasks where cost matters more, both GPUs can be effective.

On Shadeform, the RTX Pro 6000 is available from $1.25/hr. The H100 starts from $1.66/hr. Prices vary by provider, region, and contract length. Reserved commitments can reduce hourly costs significantly compared to on-demand pricing.

The RTX Pro 6000 has more VRAM at 96 GB, compared to 80 GB on the H100. Higher VRAM allows you to run larger models without quantization, use longer context windows, and process larger batch sizes — all of which improve throughput and reduce latency for memory-bound workloads.

Based on TFLOPS per dollar, the H100 offers better raw compute value at current Shadeform on-demand rates. However, the best choice depends on your specific workload — if you need the extra VRAM or throughput of the RTX Pro 6000, paying the premium may be justified by faster job completion and lower total cost.

The H100 is currently available across 13 cloud providers on Shadeform's network, compared to 7 for the RTX Pro 6000. Shadeform lets you deploy either GPU across all available providers from a single platform, so you can always find available capacity without manually checking each cloud.

Mixing different GPU types in a single training cluster is generally not recommended, as it creates performance bottlenecks where faster GPUs wait for slower ones. For best results, use a homogeneous cluster of either RTX Pro 6000 or H100. Shadeform supports on-demand clusters of up to 64 GPUs of the same type with no commitment required.

Explore RTX Pro 6000 & H100 Instances

Browse available instances with RTX Pro 6000 and H100 GPUs. Filter by provider, availability, and more to find the perfect instance for your needs.

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