Quadro RTX 3000 vs Quadro RTX 8000
The Quadro RTX 8000 has more VRAM (48GB vs 6GB), making it better suited for large models and memory-intensive workloads. Memory bandwidth runs 86% ahead (624 GB/s versus 336 GB/s), which feeds straight through into quicker inference. The Quadro RTX 3000 is $1,334 GBP cheaper than the Quadro RTX 8000.
Maximum Capacity Reached. Remove a model to add another. (2/2)
Comparable or lower specs
Quadro RTX 3000 vs Quadro RTX 8000: In-Depth Breakdown
VRAM: Quadro RTX 3000 vs Quadro RTX 8000
The Quadro RTX 8000 carries 48GB of VRAM versus 6GB on the Quadro RTX 3000. 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 42GB advantage here means the Quadro RTX 8000 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 Quadro RTX 8000 reaches 624 GB/s against 336 GB/s for the Quadro RTX 3000, a 86% advantage. Once a model is resident in VRAM, token throughput tracks this figure closely, so the Quadro RTX 8000 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 Quadro RTX 8000 delivers 14.9 TFLOPS against 5.3 TFLOPS for the Quadro RTX 3000 — a 181% compute advantage. Training runs and heavy matrix operations will complete proportionally faster on the Quadro RTX 8000.
Price & Value
Pricing starts at $613 GBP for the Quadro RTX 3000, a $1,334 GBP saving over the Quadro RTX 8000's $1,947 GBP. 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: Quadro RTX 3000 or Quadro RTX 8000?
Choose the Quadro RTX 8000 for maximum capacity — it leads on VRAM, bandwidth, and compute, making it the better fit for large models and training jobs. The Quadro RTX 3000 is the more budget-friendly option ($1,334 GBP less) — a solid choice if your models fit within its 6GB and inference volume is moderate.
Frequently Asked Questions
Can the Quadro RTX 3000 or Quadro RTX 8000 run large language models?
Which is faster for LLM inference, the Quadro RTX 3000 or the Quadro RTX 8000?
Which is better for AI training?
Which should you buy: Quadro RTX 3000 or Quadro RTX 8000?
Technical Specifications Comparison
Architecture & Cores
| Specification | Quadro RTX 3000 | Quadro RTX 8000 |
|---|---|---|
| Architecture | Turing | Turing |
| CUDA Cores (CUDA Cores / CUDA Cores) | 1,920 | 4,608✓ |
Memory
| Specification | Quadro RTX 3000 | Quadro RTX 8000 |
|---|---|---|
| VRAM Capacity | 6 GB | 48 GB✓ |
| Memory Type | GDDR6 | GDDR6 |
| Memory Bus | 192-bit | 384-bit✓ |
| Bandwidth | 336 GB/s | 624 GB/s✓ |
Connectivity & Power
| Specification | Quadro RTX 3000 | Quadro RTX 8000 |
|---|---|---|
| Interface | PCIe 3.0 x16 | PCIe 3.0 x16 |
| TDP | 160 W✓ | 295 W |
| Released | Apr 2019 | Oct 2018 |
Workstation
| Specification | Quadro RTX 3000 | Quadro RTX 8000 |
|---|---|---|
| FP32 (TFLOPS) | 5.3 TFLOPS | 14.9 TFLOPS✓ |
| ECC | Yes | Yes |
| NVLink | No | Yes✓ |
| Form factor | single-slot | dual-slot |