CUDA Cores
VRAM
GB/s
4,096
CUDA Cores
557
Base MHz
1178
Boost MHz
16GB GDDR5
512-bit bus
9
FP32 TFLOPS
18
FP16 TFLOPS
300W
TDP
0
Available Instances
$0.00/hr
Starting Price
| Architecture | Maxwell (Unknown) |
| Release Date | 2015-08-30 |
| Launch Price | $4,500.00 |
| Process | 28nm |
| Transistors | 10.4B |
none
Tensor Cores
Disabled
Transformer Engine
Not Supported
Flash Attention
10.5in
Length
4.4in
Width
2-slot
Height
The NVIDIA Tesla M60 is a powerful GPU designed for AI/ML workloads, offering exceptional performance for both training and inference tasks. With 16GB of VRAM and 4,096 CUDA cores, it provides the memory capacity and computational power needed for modern deep learning models.
Released in 2015, the Tesla M60 features Maxwell architecture with advanced AI accelerators including Tensor Cores and Transformer Engine support. This makes it ideal for large language models, computer vision tasks, and generative AI applications.
When considering cloud rental options for the Tesla M60, pricing starts at $0.00/hour from various providers. This GPU offers excellent price-to-performance for AI training workloads, with its high memory bandwidth of 320 GB/s enabling fast data transfer for large datasets.
The Tesla M60 features CUDA compute capability the latest and is compatible with all major deep learning frameworks including PyTorch, TensorFlow, and JAX. Its 28nm manufacturing process ensures efficient power consumption relative to performance output.
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
| 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.