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V100 vs L4

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

V100

The NVIDIA V100 delivers high-performance computing capabilities for AI, machine learning, and data science applications.

ManufacturerNVIDIA
GPU ArchitectureVolta
Average Price$2.21/hr
GPU VRAM16 GB
Cloud Availability3 clouds
System Memory448 GB
CPU Cores92
Storage6.0 TB

L4

The NVIDIA L4 delivers high-performance computing capabilities for AI, machine learning, and data science applications.

ManufacturerNVIDIA
GPU Architecture
Average Price$3.17/hr
GPU VRAM24 GB
Cloud Availability1 clouds
System Memory384 GB
CPU Cores64
Storage500 GB

V100 vs L4: Which Should You Choose?

The L4 offers 24 GB of VRAM — 1.5× the 16 GB on the V100 — making it better suited for large model workloads that require holding more parameters in GPU memory. On FP16 throughput, the L4 delivers 30.29 TFLOPS versus 28.26 TFLOPS on the V100 — 7% more faster for mixed-precision training and inference. Memory bandwidth favors the V100 at 0.90 TB/s compared to 0.30 TB/s on the L4, which directly impacts inference latency for memory-bandwidth-bound models. Architecturally, the V100 is built on Volta while the L4 uses Ada Lovelace, reflecting different generational capabilities and optimizations. On Shadeform, the V100 starts from $0.39/hr versus $0.90/hr for the L4 — 131% more expensive — reflecting the performance premium. The V100 is available across 3 cloud providers on Shadeform compared to 1 for the L4, giving more options for region and pricing flexibility.

V100 — Best Use Cases

  • Deep learning training
  • HPC and scientific computing
  • Legacy ML infrastructure

Choose V100 when:

  • 16 GB VRAM is sufficient for your workload
  • Cost efficiency is your primary concern
  • Your workload does not require peak FP16 throughput
  • You need flexibility across multiple cloud providers or regions

L4 — Best Use Cases

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

Choose L4 when:

  • You need 24 GB+ VRAM for large models or long context windows
  • Maximum performance justifies the higher cost
  • You are training large models or running high-throughput inference
  • Your preferred provider already has availability

See how the V100 & L4 compare

Compare detailed hardware specifications and average pricing for the V100 and L4.

Compare Hardware Specifications

V100L4
GPU Type
V100
L4
VRAM per GPU
16 GB
24 GB
Manufacturer
NVIDIA
NVIDIA
Architecture
Volta
Ada Lovelace
Interconnect
PCIe Gen3
PCIe Gen4
Memory Bandwidth
900 GB/s
300 GB/s
FP16 TFLOPS
28.26 TFLOPS (2:1)
30.29 TFLOPS (1:1)
CUDA Cores
5120
7424
Tensor Cores
640 (1st Gen)
232 (4th Gen)
RT Cores
N/A
58 (3rd Gen)
Base Clock
1230 MHz
795 MHz
Boost Clock
1380 MHz
2040 MHz
TDP
250-300W
72W
Process Node
TSMC 12nm
TSMC 4N
Data Formats
FP16, FP32, FP64
FP8, INT8, BF16, FP16, TF32, FP32

Compare Average On-Demand Pricing

V100L4
1 GPU
$1.36 /hr
$0.90 /hr
2 GPUs
$0.78 /hr
$1.72 /hr
4 GPUs
N/A
$3.37 /hr
8 GPUs
$3.76 /hr
$6.67 /hr

Frequently Asked Questions: V100 vs L4

The main differences are VRAM (16 GB vs 24 GB), FP16 throughput (28.26 vs 30.29 TFLOPS), architecture (Volta vs Ada Lovelace). The V100 uses the Volta architecture while the L4 is based on Ada Lovelace, giving each GPU different generational capabilities.

The L4 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 V100 is available from $0.39/hr. The L4 starts from $0.90/hr. Prices vary by provider, region, and contract length. Reserved commitments can reduce hourly costs significantly compared to on-demand pricing.

The L4 has more VRAM at 24 GB, compared to 16 GB on the V100. 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 V100 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 L4, paying the premium may be justified by faster job completion and lower total cost.

The V100 is currently available across 3 cloud providers on Shadeform's network, compared to 1 for the L4. 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 V100 or L4. Shadeform supports on-demand clusters of up to 64 GPUs of the same type with no commitment required.

Explore V100 & L4 Instances

Browse available instances with V100 and L4 GPUs. Filter by provider, availability, and more to find the perfect instance for your needs.

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