Comparison

NVIDIA T4 vs NVIDIA L4

Budget inference — Turing vs Ada Lovelace

The L4 delivers 1.9x the FP16 performance of the T4 (121 vs 65 TFLOPS) with 50% more memory (24GB vs 16GB) at similar power consumption. The T4 is cheaper and more widely available.

Pricing Comparison

Specifications

Specification	NVIDIA T4	NVIDIA L4
Manufacturer	NVIDIA	NVIDIA
Architecture	Turing	Ada Lovelace
Accelerator Type	GPU	GPU
Primary Use	inference	inference
Memory (VRAM)	16 GB	24 GB
FP16 Performance	65 TFLOPS	121 TFLOPS
TDP	70W	72W
Perf per Watt	0.93 TFLOPS/W	1.68 TFLOPS/W

Detailed Analysis

The T4 and L4 represent two generations of NVIDIA's energy-efficient inference GPUs. The T4 (Turing, 2018) has been the go-to budget inference GPU for years, while the L4 (Ada Lovelace, 2023) is its modern successor.

The L4's advantages are significant: 1.9x FP16 performance, 50% more memory, and Ada Lovelace's fourth-generation Tensor Cores with improved INT8 and FP8 support. Both GPUs have remarkably similar power profiles — 72W for the L4 vs 70W for the T4 — meaning the L4 delivers nearly double the performance at the same power.

The T4's enduring strength is availability and cost. It is available in virtually every cloud region globally and often costs less than half the L4's hourly rate. For lightweight inference workloads that fit in 16GB of memory, the T4 remains the most cost-effective option.

The L4's extra memory (24GB) enables it to serve larger models — up to approximately 13B parameters with quantisation, compared to the T4's ~7B limit. This makes the L4 the better choice for deploying modern language models.

Verdict

Best for Training

Neither is designed for training. For fine-tuning small models, the L4's extra memory gives it the edge.

Best for Inference

L4 for modern LLM inference (7B-13B models). T4 for lightweight models and maximum cost efficiency.

Best Value

T4 wins on raw cost per hour. L4 wins on performance per dollar for workloads that utilise its extra capability.

Frequently Asked Questions

Is the L4 worth the upgrade from T4?

Yes, if you need to serve models larger than 7B parameters or need higher throughput. The L4 delivers nearly 2x the performance at similar power. If your workload runs fine on T4, the cost savings may not justify upgrading.