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RTX 6000 vs B200

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

RTX 6000

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

ManufacturerNVIDIA
GPU Architecture
Average Price$0.50/hr
GPU VRAM24 GB
Cloud Availability1 clouds
System Memory46 GB
CPU Cores14
Storage512 GB

B200

The NVIDIA B200 delivers high-performance computing capabilities for AI, machine learning, and data science applications.

ManufacturerNVIDIA
GPU Architecture
Average Price$21.98/hr
GPU VRAM192 GB
Cloud Availability4 clouds
System Memory2900 GB
CPU Cores248
Storage30.7 TB

RTX 6000 vs B200: Which Should You Choose?

The B200 offers 192 GB of VRAM — 8× the 24 GB on the RTX 6000 — making it better suited for large model workloads that require holding more parameters in GPU memory. On FP16 throughput, the RTX 6000 delivers 32.62 TFLOPS versus 1 TFLOPS on the B200 — 33× faster for mixed-precision training and inference. Memory bandwidth favors the RTX 6000 at 0.67 TB/s compared to 0.01 TB/s on the B200, which directly impacts inference latency for memory-bandwidth-bound models. Architecturally, the RTX 6000 is built on Turing while the B200 uses Blackwell, reflecting different generational capabilities and optimizations. On Shadeform, the RTX 6000 starts from $0.50/hr versus $5.29/hr for the B200 — 958% more expensive — reflecting the performance premium. The B200 is available across 4 cloud providers on Shadeform compared to 1 for the RTX 6000, giving more options for region and pricing flexibility.

RTX 6000 — Best Use Cases

  • Inference and model serving
  • Light training and fine-tuning
  • Graphics and rendering workloads

Choose RTX 6000 when:

  • 24 GB VRAM is sufficient for your workload
  • Cost efficiency is your primary concern
  • You are training large models or running high-throughput inference
  • Your preferred provider already has availability

B200 — 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 B200 when:

  • You need 192 GB+ VRAM for large models or long context windows
  • Maximum performance justifies the higher cost
  • Your workload does not require peak FP16 throughput
  • You need flexibility across multiple cloud providers or regions

See how the RTX 6000 & B200 compare

Compare detailed hardware specifications and average pricing for the RTX 6000 and B200.

Compare Hardware Specifications

RTX 6000B200
GPU Type
RTX 6000
B200
VRAM per GPU
24 GB
192 GB
Manufacturer
NVIDIA
NVIDIA
Architecture
Turing
Blackwell
Interconnect
PCIe Gen3
SXM6
Memory Bandwidth
672 GB/s
8 TB/s
FP16 TFLOPS
32.62 TFLOPS (2:1)
1,191.2 TFLOPS (16:1)
CUDA Cores
4608
20480
Tensor Cores
576 (2nd Gen)
640 (5th Gen)
RT Cores
72 (1st Gen)
N/A
Base Clock
1440 MHz
700 MHz
Boost Clock
1770 MHz
1965 MHz
TDP
295W
1000W
Process Node
TSMC 12nm
TSMC 4NP
Data Formats
INT8, INT4, FP16, FP32
FP4, FP6, FP8, INT8, BF16, FP16, TF32, FP32, FP64

Compare Average On-Demand Pricing

RTX 6000B200
1 GPU
$0.50 /hr
$5.29 /hr
2 GPUs
N/A
$10.49 /hr
4 GPUs
N/A
$20.78 /hr
8 GPUs
N/A
$36.68 /hr

Frequently Asked Questions: RTX 6000 vs B200

The main differences are VRAM (24 GB vs 192 GB), FP16 throughput (32.62 vs 1 TFLOPS), architecture (Turing vs Blackwell). The RTX 6000 uses the Turing architecture while the B200 is based on Blackwell, giving each GPU different generational capabilities.

The RTX 6000 is generally better for large language model training due to its higher throughput and 24 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 6000 is available from $0.50/hr. The B200 starts from $5.29/hr. Prices vary by provider, region, and contract length. Reserved commitments can reduce hourly costs significantly compared to on-demand pricing.

The B200 has more VRAM at 192 GB, compared to 24 GB on the RTX 6000. 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 RTX 6000 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 B200, paying the premium may be justified by faster job completion and lower total cost.

The B200 is currently available across 4 cloud providers on Shadeform's network, compared to 1 for the RTX 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 6000 or B200. Shadeform supports on-demand clusters of up to 64 GPUs of the same type with no commitment required.

Explore RTX 6000 & B200 Instances

Browse available instances with RTX 6000 and B200 GPUs. Filter by provider, availability, and more to find the perfect instance for your needs.

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