A5000 vs RTX 4090
Explore a head to head comparison of specifications, performance, and pricing.
A5000
The NVIDIA A5000 delivers high-performance computing capabilities for AI, machine learning, and data science applications.
RTX 4090
The NVIDIA RTX 4090 delivers high-performance computing capabilities for AI, machine learning, and data science applications.
A5000 vs RTX 4090: Which Should You Choose?
Both the A5000 and RTX 4090 offer 24 GB of VRAM, putting them on equal footing for memory-bound workloads. On FP16 throughput, the RTX 4090 delivers 82.58 TFLOPS versus 27.77 TFLOPS on the A5000 — 3× faster for mixed-precision training and inference. Memory bandwidth favors the A5000 at 0.77 TB/s compared to 0.00 TB/s on the RTX 4090, which directly impacts inference latency for memory-bandwidth-bound models. Architecturally, the A5000 is built on Ampere while the RTX 4090 uses Ada Lovelace, reflecting different generational capabilities and optimizations. On Shadeform, the A5000 starts from $0.44/hr versus $0.60/hr for the RTX 4090 — 36% more expensive — reflecting the performance premium. The RTX 4090 is available across 3 cloud providers on Shadeform compared to 2 for the A5000, giving more options for region and pricing flexibility.
A5000 — Best Use Cases
- •General-purpose deep learning training
- •Fine-tuning models up to 13B parameters
- •AI inference at moderate throughput
- •Computer vision and NLP workloads
Choose A5000 when:
- ✓Cost efficiency is your primary concern
- ✓Your workload does not require peak FP16 throughput
- ✓Your preferred provider already has availability
RTX 4090 — Best Use Cases
- •LLM inference and model serving
- •Image generation and diffusion models
- •Smaller fine-tuning runs
- •Cost-efficient GPU compute
Choose RTX 4090 when:
- ✓Maximum performance justifies the higher cost
- ✓You are training large models or running high-throughput inference
- ✓You need flexibility across multiple cloud providers or regions
See how the A5000 & RTX 4090 compare
Compare detailed hardware specifications and average pricing for the A5000 and RTX 4090.
Compare Hardware Specifications
| A5000 | RTX 4090 | |
|---|---|---|
| GPU Type | A5000 | RTX 4090 |
| VRAM per GPU | 24 GB | 24 GB |
| Manufacturer | NVIDIA | NVIDIA |
| Architecture | Ampere | Ada Lovelace |
| Interconnect | PCIe Gen4 | PCIe Gen4 |
| Memory Bandwidth | 768 GB/s | 1.008 TB/s |
| FP16 TFLOPS | 27.77 TFLOPS (1:1) | 82.58 TFLOPS (1:1) |
| CUDA Cores | 8192 | 16384 |
| Tensor Cores | 256 (3rd Gen) | 512 (4th Gen) |
| RT Cores | 64 (2nd Gen) | 128 (3rd Gen) |
| Base Clock | 1170 MHz | 2235 MHz |
| Boost Clock | 1695 MHz | 2520 MHz |
| TDP | 230W | 450W |
| Process Node | TSMC 8nm | TSMC 4N |
| Data Formats | INT8, BF16, FP16, TF32, FP32 | FP8, INT8, BF16, FP16, TF32, FP32 |
Compare Average On-Demand Pricing
| A5000 | RTX 4090 | |
|---|---|---|
| 1 GPU | $0.93 /hr | $0.60 /hr |
| 2 GPUs | $1.86 /hr | $1.20 /hr |
| 4 GPUs | $3.72 /hr | $2.40 /hr |
| 8 GPUs | $3.52 /hr | $3.97 /hr |
Frequently Asked Questions: A5000 vs RTX 4090
The main differences are FP16 throughput (27.77 vs 82.58 TFLOPS), architecture (Ampere vs Ada Lovelace). The A5000 uses the Ampere architecture while the RTX 4090 is based on Ada Lovelace, giving each GPU different generational capabilities.
The RTX 4090 is generally better for large language model training due to its higher throughput and 24 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 A5000 is available from $0.44/hr. The RTX 4090 starts from $0.60/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 4090 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 A5000, paying the premium may be justified by faster job completion and lower total cost.
The RTX 4090 is currently available across 3 cloud providers on Shadeform's network, compared to 2 for the A5000. 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 A5000 or RTX 4090. Shadeform supports on-demand clusters of up to 64 GPUs of the same type with no commitment required.
Explore A5000 & RTX 4090 Instances
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