A30 vs RTX 6000
Explore a head to head comparison of specifications, performance, and pricing.
A30
The NVIDIA A30 delivers high-performance computing capabilities for AI, machine learning, and data science applications.
RTX 6000
The NVIDIA RTX 6000 delivers high-performance computing capabilities for AI, machine learning, and data science applications.
A30 vs RTX 6000: Which Should You Choose?
Both the A30 and RTX 6000 offer 24 GB of VRAM, putting them on equal footing for memory-bound workloads. On FP16 throughput, the RTX 6000 delivers 32.62 TFLOPS versus 10.32 TFLOPS on the A30 — 3× faster for mixed-precision training and inference. Memory bandwidth favors the A30 at 0.93 TB/s compared to 0.67 TB/s on the RTX 6000, which directly impacts inference latency for memory-bandwidth-bound models. Architecturally, the A30 is built on Ampere while the RTX 6000 uses Turing, reflecting different generational capabilities and optimizations. On Shadeform, the A30 starts from $0.35/hr versus $0.50/hr for the RTX 6000 — 43% more expensive — reflecting the performance premium.
A30 — 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 A30 when:
- ✓Cost efficiency is your primary concern
- ✓Your workload does not require peak FP16 throughput
RTX 6000 — Best Use Cases
- •Inference and model serving
- •Light training and fine-tuning
- •Graphics and rendering workloads
Choose RTX 6000 when:
- ✓Maximum performance justifies the higher cost
- ✓You are training large models or running high-throughput inference
See how the A30 & RTX 6000 compare
Compare detailed hardware specifications and average pricing for the A30 and RTX 6000.
Compare Hardware Specifications
| A30 | RTX 6000 | |
|---|---|---|
| GPU Type | A30 | RTX 6000 |
| VRAM per GPU | 24 GB | 24 GB |
| Manufacturer | NVIDIA | NVIDIA |
| Architecture | Ampere | Turing |
| Interconnect | PCIe Gen4 | PCIe Gen3 |
| Memory Bandwidth | 933 GB/s | 672 GB/s |
| FP16 TFLOPS | 10.32 TFLOPS (1:1) | 32.62 TFLOPS (2:1) |
| CUDA Cores | 3584 | 4608 |
| Tensor Cores | 224 (3rd Gen) | 576 (2nd Gen) |
| RT Cores | N/A | 72 (1st Gen) |
| Base Clock | 930 MHz | 1440 MHz |
| Boost Clock | 1440 MHz | 1770 MHz |
| TDP | 165W | 295W |
| Process Node | TSMC 7nm | TSMC 12nm |
| Data Formats | INT8, BF16, FP16, TF32, FP32, FP64 | INT8, INT4, FP16, FP32 |
Compare Average On-Demand Pricing
| A30 | RTX 6000 | |
|---|---|---|
| 1 GPU | $0.35 /hr | $0.50 /hr |
| 2 GPUs | $0.70 /hr | N/A |
| 4 GPUs | $1.40 /hr | N/A |
| 8 GPUs | $2.80 /hr | N/A |
Frequently Asked Questions: A30 vs RTX 6000
The main differences are FP16 throughput (10.32 vs 32.62 TFLOPS), architecture (Ampere vs Turing). The A30 uses the Ampere architecture while the RTX 6000 is based on Turing, giving each GPU different generational capabilities.
The RTX 6000 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 A30 is available from $0.35/hr. The RTX 6000 starts from $0.50/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 6000 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 A30, paying the premium may be justified by faster job completion and lower total cost.
The A30 is currently available across 1 cloud providers on Shadeform's network, compared to 1 for the RTX 6000. 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 A30 or RTX 6000. Shadeform supports on-demand clusters of up to 64 GPUs of the same type with no commitment required.
Explore A30 & RTX 6000 Instances
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