Is the Quadro RTX 5880 Ada 48GB Any Good?
More RAM, less power, and still expensive as...
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The NVIDIA RTX 5880 Ada Generation (often called “Quadro” in previous branding) is a high-end professional workstation GPU released in early 2024. It features 48GB of GDDR6 ECC memory, 14,080 CUDA cores, and is built on the Ada Lovelace architecture. This card primarily targets professional workloads such as AI, deep learning, 3D rendering, and advanced visualization.
Performance - RTX 5880 Ada
- Raw Power: The RTX 5880 Ada offers 69.3 FP32 TFLOPS and 554 FP8 TFLOPS, which is strong for professional workloads but notably less than the flagship RTX 6000 Ada (91.1 FP32 TFLOPS).
- VRAM: With 48GB of VRAM, it is well-suited for large AI models, high-resolution rendering, and data-intensive applications.
- Efficiency: Built on a 5nm process, it is more power-efficient and modern than previous generations, with a 285W TDP.
Comparison to Other Cards
| Feature | RTX 5880 Ada | RTX 6000 Ada | RTX A6000 (Ampere) |
|---|---|---|---|
| CUDA Cores | 14,080 | 18,176 | 10,752 |
| VRAM | 48GB GDDR6 ECC | 48GB GDDR6 ECC | 48GB GDDR6 ECC |
| FP32 TFLOPS | 69.3 | 91.1 | 38.7 |
| Power Consumption | 285W | 300W | 300W |
| Release | Jan 2024 | 2022 | 2020 |
- Performance: The RTX 5880 Ada is about 5% faster than the previous-generation RTX A6000 (Ampere), but significantly slower than the RTX 6000 Ada.
- Use Case: The 5880 Ada is best viewed as a mid-high tier workstation card, sitting between the RTX 6000 Ada and the RTX 5000 Ada in both price and performance.
Special Considerations
- Export Compliance: The RTX 5880 Ada was specifically designed to comply with US export regulations, making it available in markets (like China) where the RTX 6000 Ada is restricted.
- Price: The card is expected to be expensive (estimates around $6,800 USD), similar to other high-end workstation GPUs.
- Target Audience: This is not a consumer gaming card. It is aimed at professionals who need large VRAM and workstation features for AI, simulation, or content creation.
Pros & Cons
Pros
- Massive 48GB VRAM for large datasets and AI models
- Modern Ada Lovelace architecture (efficient, advanced features)
- Good performance for professional workloads
- Global availability, including markets with export restrictions
Cons
- Significantly slower than the RTX 6000 Ada despite similar VRAM
- Very expensive compared to consumer GPUs
- Not intended for gaming; overkill for most non-professional users
RTX 5880 Ada vs RTX 6000 Ada in Real AI Tasks
Performance Comparison
- The RTX 6000 Ada is significantly more powerful than the RTX 5880 Ada for AI workloads. The RTX 6000 Ada features 18,176 CUDA cores and delivers 91.1 TFLOPS of single-precision performance, while the RTX 5880 Ada has 14,080 CUDA cores and achieves 69.3 TFLOPS (based on standard specs and generational differences).
- Both cards offer 48GB of GDDR6 ECC memory, making them suitable for large AI models and datasets.
- The RTX 6000 Ada also boasts higher memory bandwidth (960 GB/s), which benefits memory-intensive AI tasks.
AI Training and Inference
- For demanding AI training and inference, the RTX 6000 Ada’s higher core count and greater tensor performance (up to 1.45 PFLOPS) give it a clear edge over the RTX 5880 Ada.
- In practical terms, this means the RTX 6000 Ada will train large neural networks faster and handle more complex models or larger batch sizes before running into performance bottlenecks.
Efficiency and Use Case
- Both GPUs are built on the Ada Lovelace architecture and are highly efficient, but the RTX 6000 Ada offers better performance per watt due to its higher computational throughput.
- The RTX 5880 Ada is positioned as a slightly lower-tier alternative, often chosen in regions where the RTX 6000 Ada is restricted due to export controls, or where budget is a concern.
Summary Table
| Feature | RTX 5880 Ada | RTX 6000 Ada |
|---|---|---|
| CUDA Cores | 14,080 | 18,176 |
| FP32 TFLOPS | 69.3 | 91.1 |
| Tensor Perf (PFLOPS) | ~1.1 (est.) | 1.45 |
| VRAM | 48GB GDDR6 ECC | 48GB GDDR6 ECC |
| Memory Bandwidth | ~800 GB/s (est.) | 960 GB/s |
| Architecture | Ada Lovelace | Ada Lovelace |
Is the Cost Difference Justified by Performance Gains for Professional AI Workloads?
TL;DR:
For most professional AI workloads, the cost difference between the RTX 5880 Ada and the RTX 6000 Ada is only justified if your projects consistently require the highest levels of performance, throughput, and efficiency. The RTX 6000 Ada delivers significantly better performance, but at a premium price that may not yield proportional returns for all use cases.
Key Considerations
-
Performance Scaling vs. Cost
The RTX 6000 Ada outperforms the RTX 5880 Ada in AI training and inference due to its higher core count and better memory bandwidth. This results in faster model training and the ability to handle larger or more complex AI tasks. However, the performance increase is not linear with the price—the RTX 6000 Ada is considerably more expensive, and the incremental gains may diminish depending on your specific workload and how well your pipeline is optimized. -
Cost Optimization
AI workload costs are highly sensitive to optimization strategies. Efficient use of resources, such as batching, caching, and workload scheduling, can often yield substantial cost savings without requiring the absolute top-tier GPU. For many organizations, investing in optimization and workflow improvements may provide better ROI than simply buying the most expensive hardware. -
Budget and Use Case
If your business or research requires the fastest possible turnaround for large-scale models, or if GPU time is a critical bottleneck, the RTX 6000 Ada’s premium may be justified. For most professional teams, however, the RTX 5880 Ada offers a better balance of performance and cost, especially if you can optimize your workloads or if your models do not consistently saturate the GPU. -
Total Cost of Ownership
The hardware price is just one component. Ongoing operational costs, including power, cooling, integration, and maintenance, must be factored in. The higher power draw and infrastructure requirements of the RTX 6000 Ada can further increase total costs.
Summary Table: Performance vs Cost: RTX 5880 Ada vs RTX 6000 Ada
| GPU | Performance (AI) | Cost | Value for Money | Best For |
|---|---|---|---|---|
| RTX 5880 Ada | High | Lower | Strong | Most pro AI workloads, budget-conscious teams |
| RTX 6000 Ada | Very High | Much Higher | Moderate | Mission-critical, time-sensitive, or ultra-large workloads |
Conclusion
The Quadro RTX 5880 Ada 48GB is a powerful, modern workstation GPU with a huge memory buffer, ideal for professionals in AI, rendering, and visualization who need large VRAM and reliable performance. However, it is notably less powerful than the RTX 6000 Ada and is priced similarly, making it less attractive unless you specifically need a card that complies with export restrictions or require the VRAM for specialized workloads. For most users outside of these niches, other GPUs may offer better value for money.
For real AI tasks—especially those involving large models, deep learning training, or high-throughput inference—the RTX 6000 Ada delivers noticeably better performance than the RTX 5880 Ada due to its higher core count, faster memory, and superior tensor processing capabilities. The RTX 5880 Ada is still a strong choice for professional AI workloads, but the RTX 6000 Ada remains the top performer in this segment.
The RTX 6000 Ada’s higher cost is justified only for organizations where maximum performance directly translates to significant business or research value, such as in large research labs or enterprises with massive AI workloads. For most professional users, careful workload optimization and the RTX 5880 Ada will deliver better overall value.
