RTX A1000 vs RTX A400
The RTX A1000 has more VRAM (8GB vs 4GB), making it better suited for large models and memory-intensive workloads. Memory bandwidth runs 75% ahead (224 GB/s versus 128 GB/s), which feeds straight through into quicker inference. The RTX A400 is $3,969 SEK cheaper than the RTX A1000.
Maximum Capacity Reached. Remove a model to add another. (2/2)
Comparable or lower specs
RTX A1000 vs RTX A400: In-Depth Breakdown
VRAM: RTX A1000 vs RTX A400
The RTX A1000 carries 8GB 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 4GB advantage here means the RTX A1000 can run larger models natively and handle bigger batch sizes in production.
Inference Speed: Memory Bandwidth
The rate data moves to the compute units — memory bandwidth — is what caps autoregressive inference speed (token generation in LLMs). Here the RTX A1000 reaches 224 GB/s against 128 GB/s for the RTX A400, a 75% advantage. Once a model is resident in VRAM, token throughput tracks this figure closely, so the RTX A1000 generates tokens proportionally faster on bandwidth-bound workloads.
AI Training & Compute
For model training, scientific simulation, and rendering, FP32 throughput is the key metric. The RTX A1000 delivers 6 TFLOPS against 3 TFLOPS for the RTX A400 — a 100% compute advantage. Training runs and heavy matrix operations will complete proportionally faster on the RTX A1000.
Price & Value
Pricing starts at $2,530 SEK for the RTX A400, a $3,969 SEK saving over the RTX A1000's $6,499 SEK. Teams working within a tighter budget may find that saving worth more than the spec gap, particularly if the smaller card already covers their typical workload.
Which should you buy: RTX A1000 or RTX A400?
Choose the RTX A1000 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 ($3,969 SEK less) — a solid choice if your models fit within its 4GB and inference volume is moderate.
Frequently Asked Questions
Can the RTX A1000 or RTX A400 run large language models?
Which is faster for LLM inference, the RTX A1000 or the RTX A400?
Which is better for AI training?
Which should you buy: RTX A1000 or RTX A400?
Technical Specifications Comparison
Architecture & Cores
| Specification | RTX A1000 | RTX A400 |
|---|---|---|
| Architecture | Ada Lovelace | Ada Lovelace |
| CUDA Cores (CUDA Cores / CUDA Cores) | 1,280✓ | 768 |
Memory
| Specification | RTX A1000 | RTX A400 |
|---|---|---|
| VRAM Capacity | 8 GB✓ | 4 GB |
| Memory Type | GDDR6 | GDDR6 |
| Memory Bus | 128-bit✓ | 64-bit |
| Bandwidth | 224 GB/s✓ | 128 GB/s |
Connectivity & Power
| Specification | RTX A1000 | RTX A400 |
|---|---|---|
| Interface | PCIe 4.0 x16 | PCIe 4.0 x16 |
| TDP | 50 W | 50 W |
| Released | Aug 2023 | Aug 2023 |
Workstation
| Specification | RTX A1000 | RTX A400 |
|---|---|---|
| FP32 (TFLOPS) | 6 TFLOPS✓ | 3 TFLOPS |
| ECC | Yes | Yes |
| NVLink | No | No |
| Form factor | low-profile | low-profile |