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B200 vs L40

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

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

L40

The NVIDIA L40 delivers high-performance computing capabilities for AI, machine learning, and data science applications.

ManufacturerNVIDIA
GPU Architecture
Average Price$3.42/hr
GPU VRAM48 GB
Cloud Availability2 clouds
System Memory768 GB
CPU Cores252
Storage6.6 TB

B200 vs L40: Which Should You Choose?

The B200 offers 192 GB of VRAM — 4× the 48 GB on the L40 — making it better suited for large model workloads that require holding more parameters in GPU memory. On FP16 throughput, the L40 delivers 90.52 TFLOPS versus 1 TFLOPS on the B200 — 91× faster for mixed-precision training and inference. Memory bandwidth favors the L40 at 0.86 TB/s compared to 0.01 TB/s on the B200, which directly impacts inference latency for memory-bandwidth-bound models. Architecturally, the B200 is built on Blackwell while the L40 uses Ada Lovelace, reflecting different generational capabilities and optimizations. On Shadeform, the L40 starts from $0.99/hr versus $5.29/hr for the B200 — 434% more expensive — reflecting the performance premium. The B200 is available across 4 cloud providers on Shadeform compared to 2 for the L40, giving more options for region and pricing flexibility.

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

L40 — Best Use Cases

  • LLM inference and model serving
  • Image generation and diffusion models
  • Smaller fine-tuning runs
  • Cost-efficient GPU compute

Choose L40 when:

  • 48 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

See how the B200 & L40 compare

Compare detailed hardware specifications and average pricing for the B200 and L40.

Compare Hardware Specifications

B200L40
GPU Type
B200
L40
VRAM per GPU
192 GB
48 GB
Manufacturer
NVIDIA
NVIDIA
Architecture
Blackwell
Ada Lovelace
Interconnect
SXM6
PCIe Gen4
Memory Bandwidth
8 TB/s
864 GB/s
FP16 TFLOPS
1,191.2 TFLOPS (16:1)
90.52 TFLOPS (1:1)
CUDA Cores
20480
18176
Tensor Cores
640 (5th Gen)
568 (4th Gen)
RT Cores
N/A
142 (3rd Gen)
Base Clock
700 MHz
735 MHz
Boost Clock
1965 MHz
2490 MHz
TDP
1000W
300W
Process Node
TSMC 4NP
TSMC 4N
Data Formats
FP4, FP6, FP8, INT8, BF16, FP16, TF32, FP32, FP64
FP8, INT8, BF16, FP16, TF32, FP32

Compare Average On-Demand Pricing

B200L40
1 GPU
$5.29 /hr
$0.99 /hr
2 GPUs
$10.49 /hr
$1.99 /hr
4 GPUs
$20.78 /hr
$4.98 /hr
8 GPUs
$36.68 /hr
$8.00 /hr

Frequently Asked Questions: B200 vs L40

The main differences are VRAM (192 GB vs 48 GB), FP16 throughput (1 vs 90.52 TFLOPS), architecture (Blackwell vs Ada Lovelace). The B200 uses the Blackwell architecture while the L40 is based on Ada Lovelace, giving each GPU different generational capabilities.

The L40 is generally better for large language model training due to its higher throughput and 48 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 L40 is available from $0.99/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 48 GB on the L40. 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 L40 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 2 for the L40. 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 B200 or L40. Shadeform supports on-demand clusters of up to 64 GPUs of the same type with no commitment required.

Explore B200 & L40 Instances

Browse available instances with B200 and L40 GPUs. Filter by provider, availability, and more to find the perfect instance for your needs.

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