RTX 4000 Ada vs RTX 4000 Ada
Explore a head to head comparison of specifications, performance, and pricing.
RTX 4000 Ada
The NVIDIA RTX 4000 Ada delivers high-performance computing capabilities for AI, machine learning, and data science applications.
RTX 4000 Ada
The NVIDIA RTX 4000 Ada delivers high-performance computing capabilities for AI, machine learning, and data science applications.
RTX 4000 Ada vs RTX 4000 Ada: Which Should You Choose?
Both the RTX 4000 Ada and RTX 4000 Ada offer 20 GB of VRAM, putting them on equal footing for memory-bound workloads.
RTX 4000 Ada — Best Use Cases
- •LLM inference and model serving
- •Image generation and diffusion models
- •Smaller fine-tuning runs
- •Cost-efficient GPU compute
Choose RTX 4000 Ada when:
- ✓The RTX 4000 Ada fits your infrastructure and budget
RTX 4000 Ada — Best Use Cases
- •LLM inference and model serving
- •Image generation and diffusion models
- •Smaller fine-tuning runs
- •Cost-efficient GPU compute
Choose RTX 4000 Ada when:
- ✓The RTX 4000 Ada fits your infrastructure and budget
See how the RTX 4000 Ada & RTX 4000 Ada compare
Compare detailed hardware specifications and average pricing for the RTX 4000 Ada and RTX 4000 Ada.
Compare Hardware Specifications
| RTX 4000 Ada | RTX 4000 Ada | |
|---|---|---|
| GPU Type | RTX 4000 Ada | RTX 4000 Ada |
| VRAM per GPU | 20 GB | 20 GB |
| Manufacturer | NVIDIA | NVIDIA |
| Architecture | Ada Lovelace | Ada Lovelace |
| Interconnect | PCIe Gen4 | PCIe Gen4 |
| Memory Bandwidth | 360 GB/s | 360 GB/s |
| FP16 TFLOPS | 26.73 TFLOPS (1:1) | 26.73 TFLOPS (1:1) |
| CUDA Cores | 6144 | 6144 |
| Tensor Cores | 192 (4th Gen) | 192 (4th Gen) |
| RT Cores | 48 (3rd Gen) | 48 (3rd Gen) |
| Base Clock | 1500 MHz | 1500 MHz |
| Boost Clock | 2175 MHz | 2175 MHz |
| TDP | 130W | 130W |
| Process Node | TSMC 4N | TSMC 4N |
| Data Formats | FP8, INT8, BF16, FP16, TF32, FP32 | FP8, INT8, BF16, FP16, TF32, FP32 |
Compare Average On-Demand Pricing
| RTX 4000 Ada | RTX 4000 Ada | |
|---|---|---|
| 1 GPU | $0.79 /hr | $0.79 /hr |
| 2 GPUs | N/A | N/A |
| 4 GPUs | N/A | N/A |
| 8 GPUs | N/A | N/A |
Frequently Asked Questions: RTX 4000 Ada vs RTX 4000 Ada
The RTX 4000 Ada and RTX 4000 Ada have different specifications and performance characteristics suited to different workloads. Use the spec comparison table above for a detailed breakdown.
The RTX 4000 Ada is generally better for large language model training due to its higher throughput and 20 GB of VRAM, which allows fitting larger models or larger batch sizes in a single pass. For smaller models or fine-tuning tasks where cost matters more, both GPUs can be effective.
On Shadeform, the RTX 4000 Ada is available from $0.79/hr. The RTX 4000 Ada starts from $0.79/hr. Prices vary by provider, region, and contract length. Reserved commitments can reduce hourly costs significantly compared to on-demand pricing.
Based on TFLOPS per dollar, the RTX 4000 Ada offers better raw compute value at current Shadeform on-demand rates. However, the best choice depends on your specific workload — if you need the extra VRAM or throughput of the RTX 4000 Ada, paying the premium may be justified by faster job completion and lower total cost.
The RTX 4000 Ada is currently available across 1 cloud providers on Shadeform's network, compared to 1 for the RTX 4000 Ada. Shadeform lets you deploy either GPU across all available providers from a single platform, so you can always find available capacity without manually checking each cloud.
Mixing different GPU types in a single training cluster is generally not recommended, as it creates performance bottlenecks where faster GPUs wait for slower ones. For best results, use a homogeneous cluster of either RTX 4000 Ada or RTX 4000 Ada. Shadeform supports on-demand clusters of up to 64 GPUs of the same type with no commitment required.
Explore RTX 4000 Ada & RTX 4000 Ada Instances
Browse available instances with RTX 4000 Ada and RTX 4000 Ada GPUs. Filter by provider, availability, and more to find the perfect instance for your needs.
Explore more GPU comparisons
Select any two GPUs to compare their specifications and explore pricing across providers.