NVIDIA RTX 2070
2,304
CUDA Cores
8GB
VRAM
448
GB/s
Technical Specifications
2,304
CUDA Cores
1410
Base MHz
1620
Boost MHz
8GB GDDR6
256-bit bus
Performance
7.5
FP32 TFLOPS
14.9
FP16 TFLOPS
175W
TDP
Cloud Availability
1
Available Instances
$0.03/hr
Starting Price
Detailed Specifications
| Architecture | Turing (Unknown) |
| Release Date | 2018-10-17 |
| Launch Price | $499.00 |
| Process | 12nm |
| Transistors | 10.8B |
AI Features
Gen 2
Tensor Cores
Disabled
Transformer Engine
Not Supported
Flash Attention
Physical Specifications
Dimensions
9.0in
Length
4.4in
Width
2-slot
Height
About RTX 2070 GPU
The NVIDIA RTX 2070 is a powerful GPU designed for AI/ML workloads, offering exceptional performance for both training and inference tasks. With 8GB of VRAM and 2,304 CUDA cores, it provides the memory capacity and computational power needed for modern deep learning models.
Released in 2018, the RTX 2070 features Turing 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 RTX 2070, pricing starts at $0.03/hour from various providers. This GPU offers excellent price-to-performance for AI training workloads, with its high memory bandwidth of 448 GB/s enabling fast data transfer for large datasets.
The RTX 2070 features CUDA compute capability the latest and is compatible with all major deep learning frameworks including PyTorch, TensorFlow, and JAX. Its 12nm manufacturing process ensures efficient power consumption relative to performance output.
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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 RTX 2070
Complete Specifications for the NVIDIA RTX 2070
Get detailed technical specifications for the NVIDIA RTX 2070 including VRAM capacity of , CUDA core count, Tensor Core count, memory bandwidth, and CUDA compute capability of . This GPU is designed for demanding AI training, inference, and high-performance computing workloads. Understanding these specifications helps you determine whether it is the right fit for PyTorch, TensorFlow, or custom CUDA-based applications.
Compare NVIDIA RTX 2070 Cloud Rental Prices per Hour
Find the best cloud rental prices for the NVIDIA RTX 2070 across providers like RunPod, Vast.ai, Lambda Labs, and CoreWeave. GPUvec aggregates real-time pricing data so you can compare costs per hour, find available instances, and choose the most cost-effective provider. GPU cloud pricing for this model varies by region and instance type, so comparing multiple options can save significantly on compute costs.
Is the NVIDIA RTX 2070 the Right GPU for Your AI Workload?
Learn whether the NVIDIA RTX 2070 is the right choice for your specific AI and ML workloads. We cover use cases including large language model training, fine-tuning, inference serving, computer vision, scientific computing, and rendering. Compare its specifications and pricing against other GPUs like the H100, A100, and RTX 5090 to make an informed decision for your infrastructure needs.
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 |
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