NVIDIA Tesla T4
2,560
CUDA Cores
16GB
VRAM
320
GB/s
Technical Specifications
2,560
CUDA Cores
585
Base MHz
1590
Boost MHz
16GB GDDR6
256-bit bus
Performance
8.1
FP32 TFLOPS
65
FP16 TFLOPS
70W
TDP
Cloud Availability
1
Available Instances
$0.27/hr
Starting Price
Detailed Specifications
| Architecture | Turing (Unknown) |
| Release Date | 2018-09-13 |
| Launch Price | $2,299.00 |
| Process | 12nm |
| Transistors | 13.6B |
AI Features
Gen 2
Tensor Cores
Disabled
Transformer Engine
Not Supported
Flash Attention
Physical Specifications
Dimensions
6.6in
Length
4.4in
Width
1-slot
Height
About Tesla T4 GPU
The NVIDIA Tesla T4 was introduced in 2018 on the Turing architecture. Its specification combines 2,560 CUDA cores with 16GB of GDDR6, which defines both the workloads it can run and the batch sizes it can hold.
Based on its 16GB memory capacity, the Tesla T4 is best evaluated for quantized language-model inference, image generation, and medium-sized training jobs. Always size the model, optimizer state, KV cache, and framework overhead together rather than choosing a GPU from core count alone.
GPUvec currently tracks 1 cloud listing for the Tesla T4, with the lowest observed hourly rate at $0.27. Prices and availability can change by provider, region, and instance configuration, so verify the final rate before starting a workload.
For software planning, the Tesla T4 combines 320 GB/s of memory bandwidth, CUDA compute capability 7.5, and a 12nm manufacturing process. Confirm the minimum CUDA, PyTorch, TensorFlow, or driver version required by your application before renting or purchasing hardware.
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External Resources
Learn more about GPUs from these authoritative sources:
Official CUDA programming guide
NVIDIA GPU Specifications →Official NVIDIA GPU specs
TechPowerUp GPU Database →Comprehensive GPU specifications
CUDA Compute Capability Guide →GPU compute capability reference
What You Need to Know About the Tesla T4
Complete Specifications for the NVIDIA Tesla T4
The NVIDIA Tesla T4 uses the Turing architecture and combines 2,560 CUDA cores with 16GB of GDDR6. GPUvec records 320 GB/s memory bandwidth alongside architecture, release date, process node, accelerator features, and physical specifications so the page can be evaluated from source data instead of model-name assumptions.
Compare NVIDIA Tesla T4 Cloud Rental Prices per Hour
GPUvec currently tracks 1 cloud listing, with an observed starting rate of $0.27 per hour. Provider rates can vary by region, host configuration, billing model, and availability. Use the provider directory and related-GPU links to compare an available alternative when this exact accelerator is not listed.
Is the NVIDIA Tesla T4 the Right GPU for Your AI Workload?
Start with the 16GB memory limit, then evaluate 320 GB/s memory bandwidth, compute features, and software compatibility for your workload. Model weights, KV cache, activations, optimizer state, and framework overhead all consume memory. Compare this page with related accelerators rather than assuming that a higher core count alone guarantees a better training or inference result.
Top GPUs for Training and Inference
| Category | Rank 1 | Rank 2 | Rank 3 |
|---|---|---|---|
| Best for Training | NVIDIA H200 | NVIDIA H100 | NVIDIA B200 |
| Best for Inference | NVIDIA A40 | NVIDIA A100 | NVIDIA A10 |
Compare GPU specifications and cloud instances to find the best GPU for your workload.