RTX 6000 vs A30
Explore a head to head comparison of specifications, performance, and pricing.
RTX 6000
The NVIDIA RTX 6000 delivers high-performance computing capabilities for AI, machine learning, and data science applications.
A30
The NVIDIA A30 delivers high-performance computing capabilities for AI, machine learning, and data science applications.
RTX 6000 vs A30: Which Should You Choose?
Both the RTX 6000 and A30 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 RTX 6000 is built on Turing while the A30 uses Ampere, 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.
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
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
See how the RTX 6000 & A30 compare
Compare detailed hardware specifications and average pricing for the RTX 6000 and A30.
Compare Hardware Specifications
| RTX 6000 | A30 | |
|---|---|---|
| GPU Type | RTX 6000 | A30 |
| VRAM per GPU | 24 GB | 24 GB |
| Manufacturer | NVIDIA | NVIDIA |
| Architecture | Turing | Ampere |
| Interconnect | PCIe Gen3 | PCIe Gen4 |
| Memory Bandwidth | 672 GB/s | 933 GB/s |
| FP16 TFLOPS | 32.62 TFLOPS (2:1) | 10.32 TFLOPS (1:1) |
| CUDA Cores | 4608 | 3584 |
| Tensor Cores | 576 (2nd Gen) | 224 (3rd Gen) |
| RT Cores | 72 (1st Gen) | N/A |
| Base Clock | 1440 MHz | 930 MHz |
| Boost Clock | 1770 MHz | 1440 MHz |
| TDP | 295W | 165W |
| Process Node | TSMC 12nm | TSMC 7nm |
| Data Formats | INT8, INT4, FP16, FP32 | INT8, BF16, FP16, TF32, FP32, FP64 |
Compare Average On-Demand Pricing
| RTX 6000 | A30 | |
|---|---|---|
| 1 GPU | $0.50 /hr | $0.35 /hr |
| 2 GPUs | N/A | $0.70 /hr |
| 4 GPUs | N/A | $1.40 /hr |
| 8 GPUs | N/A | $2.80 /hr |
Frequently Asked Questions: RTX 6000 vs A30
The main differences are FP16 throughput (32.62 vs 10.32 TFLOPS), architecture (Turing vs Ampere). The RTX 6000 uses the Turing architecture while the A30 is based on Ampere, 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 RTX 6000 is currently available across 1 cloud providers on Shadeform's network, compared to 1 for the A30. 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 6000 or A30. Shadeform supports on-demand clusters of up to 64 GPUs of the same type with no commitment required.
Explore RTX 6000 & A30 Instances
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