NVIDIA RTX 5070
6,144
CUDA Cores
12GB
VRAM
672
GB/s
Technical Specifications
6,144
CUDA Cores
2160
Base MHz
2512
Boost MHz
12GB GDDR7
192-bit bus
Performance
30
FP32 TFLOPS
60
FP16 TFLOPS
250W
TDP
Cloud Availability
0
Available Instances
$0.00/hr
Starting Price
Detailed Specifications
| Architecture | Blackwell (Unknown) |
| Release Date | 2025-02-20 |
| Launch Price | $549.00 |
| Process | 4nm |
| Transistors | 31.1B |
AI Features
Gen 5
Tensor Cores
Disabled
Transformer Engine
Not Supported
Flash Attention
Physical Specifications
Dimensions
10.5in
Length
4.4in
Width
2-slot
Height
About RTX 5070 GPU
The NVIDIA RTX 5070 was introduced in 2025 on the Blackwell architecture. Its specification combines 6,144 CUDA cores and 192 Tensor Cores with 12GB of GDDR7, which defines both the workloads it can run and the batch sizes it can hold.
Based on its 12GB memory capacity, the RTX 5070 is best evaluated for budget inference, computer vision, local development, and carefully sized fine-tuning jobs. Always size the model, optimizer state, KV cache, and framework overhead together rather than choosing a GPU from core count alone.
GPUvec does not currently have an active hourly cloud listing for the RTX 5070. This is not a zero-dollar offer: it means no comparable provider price is available in the present dataset. Check the provider directory for availability or compare a related GPU with an active listing.
For software planning, the RTX 5070 combines 672 GB/s of memory bandwidth, CUDA compute capability the latest, and a 4nm manufacturing process. Confirm the minimum CUDA, PyTorch, TensorFlow, or driver version required by your application before renting or purchasing hardware.
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 5070
Complete Specifications for the NVIDIA RTX 5070
The NVIDIA RTX 5070 uses the Blackwell architecture and combines 6,144 CUDA cores with 12GB of GDDR7. GPUvec records 672 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 RTX 5070 Cloud Rental Prices per Hour
GPUvec currently has no comparable active hourly listing for this model; this means pricing is unavailable, not free. 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 RTX 5070 the Right GPU for Your AI Workload?
Start with the 12GB memory limit, then evaluate 672 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.