GPU Comparison
Select up to 2 GPUs to analyze their pricing, performance, and specifications side-by-side.
The RTX PRO 6000 Blackwell has more VRAM (96GB vs 4GB), making it better suited for large models and memory-intensive workloads. Its memory bandwidth is 1300% higher (1792 GB/s vs 128 GB/s), translating directly to faster inference throughput. The RTX A400 is $11,651 USD cheaper than the RTX PRO 6000 Blackwell.
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Comparable or lower specs
RTX A400 vs RTX PRO 6000 Blackwell: In-Depth Breakdown
VRAM: RTX A400 vs RTX PRO 6000 Blackwell
The RTX PRO 6000 Blackwell carries 96GB of VRAM versus 4GB on the RTX A400. VRAM capacity is the primary constraint for running AI models without quantization — a 70B-parameter model in FP16 requires roughly 140GB, and even smaller models benefit from extra headroom. The 92GB advantage here means the RTX PRO 6000 Blackwell can run larger models natively and handle bigger batch sizes in production.
Inference Speed: Memory Bandwidth
Memory bandwidth determines how quickly data is fed to the compute units — it's the main bottleneck for autoregressive inference (token generation in LLMs). The RTX PRO 6000 Blackwell delivers 1792 GB/s versus 128 GB/s on the RTX A400, a 1300% edge. For models already loaded into VRAM, token generation speed scales closely with this number: the RTX PRO 6000 Blackwell will produce tokens proportionally faster in bandwidth-bound workloads.
AI Training & Compute
For model training, scientific simulation, and rendering, FP32 throughput is the key metric. The RTX PRO 6000 Blackwell delivers 125 TFLOPS against 3 TFLOPS for the RTX A400 — a 4067% compute advantage. Training runs and heavy matrix operations will complete proportionally faster on the RTX PRO 6000 Blackwell.
Price & Value
The RTX A400 lists from $179 USD, $11,651 USD less than the RTX PRO 6000 Blackwell at $11,830 USD. For budget-constrained teams, the savings may outweigh the spec gap — especially if the smaller card covers your typical workload.
Which should you buy: RTX A400 or RTX PRO 6000 Blackwell?
Choose the RTX PRO 6000 Blackwell for maximum capacity — it leads on VRAM, bandwidth, and compute, making it the better fit for large models and training jobs. The RTX A400 is the more budget-friendly option ($11,651 USD less) — a solid choice if your models fit within its 4GB and inference volume is moderate.
Frequently Asked Questions
Can the RTX A400 or RTX PRO 6000 Blackwell run large language models?
Which is faster for LLM inference, the RTX A400 or the RTX PRO 6000 Blackwell?
Which is better for AI training?
Technical Specifications Comparison
Architecture & Cores
| Specification | RTX A400 | RTX PRO 6000 Blackwell |
|---|---|---|
| Architecture | Ada Lovelace | Blackwell |
| CUDA Cores (CUDA Cores / CUDA Cores) | 768 | 24,064✓ |
Memory
| Specification | RTX A400 | RTX PRO 6000 Blackwell |
|---|---|---|
| VRAM Capacity | 4 GB | 96 GB✓ |
| Memory Type | GDDR6 | GDDR7 |
| Memory Bus | 64-bit | 512-bit✓ |
| Bandwidth | 128 GB/s | 1,792 GB/s✓ |
Connectivity & Power
| Specification | RTX A400 | RTX PRO 6000 Blackwell |
|---|---|---|
| Interface | PCIe 4.0 x16 | PCIe 5.0 x16 |
| TDP | 50 W✓ | 600 W |
| Released | Aug 2023 | Mar 2025 |
Workstation
| Specification | RTX A400 | RTX PRO 6000 Blackwell |
|---|---|---|
| FP32 (TFLOPS) | 3 TFLOPS | 125 TFLOPS✓ |
| ECC | Yes | Yes |
| NVLink | No | No |
| Form factor | low-profile | dual-slot |