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NVIDIA RTX 3090 Server
NVIDIA RTX 3090 Server is a value-oriented GPU cloud server available from Immers Cloud. The RTX 3090 offers 24 GB GDDR6X VRAM at a budget-friendly price point, making it a popular choice for ML workloads that need VRAM capacity over raw speed.
Specifications
| Component | Specification |
|---|---|
| GPU | NVIDIA GeForce RTX 3090 (Ampere architecture) |
| VRAM | 24 GB GDDR6X |
| CUDA Cores | 10,496 |
| Memory Bandwidth | 936 GB/s |
| Tensor Cores | 3rd Generation |
| TDP | 350W |
| Starting Price | From $0.75/hr |
Performance
The RTX 3090 remains highly relevant thanks to its 24 GB VRAM at an affordable price:
- 24 GB GDDR6X — same VRAM capacity as RTX 4090, enough for most models
- 10,496 CUDA cores with Ampere architecture
- 3rd-gen Tensor Cores — FP16, BF16, TF32, INT8 support
- 936 GB/s bandwidth — close to the RTX 4090's 1,008 GB/s
Compared to the NVIDIA RTX 4090 Server ($0.93/hr):
- ~50% slower for raw compute
- Same 24 GB VRAM capacity
- 19% cheaper per hour
- Better value when VRAM matters more than speed
For many inference workloads, the RTX 3090 performs similarly to the 4090 since inference is often memory-bound rather than compute-bound.
Best Use Cases
- Budget ML training and fine-tuning
- LLM inference with quantization
- AI image generation (Stable Diffusion, Flux)
- VRAM-hungry workloads on a budget
- Computer vision model training
- ML prototyping and experimentation
- Video upscaling and AI enhancement
Pros and Cons
Advantages
- $0.75/hr — very affordable for 24 GB VRAM
- Same VRAM capacity as RTX 4090
- Ampere Tensor Cores for accelerated ML
- Good bandwidth for inference workloads
- Proven platform with mature driver support
Limitations
- ~50% slower compute than RTX 4090
- Previous-gen Ampere architecture (no FP8)
- No ECC memory or NVLink
- Higher power consumption relative to performance
- 350W TDP
Pricing
Available from Immers Cloud starting at $0.75/hr. Monthly cost for 24/7: approximately $540.
Recommendation
The NVIDIA RTX 3090 Server is the value king for users who need 24 GB VRAM without paying RTX 4090 prices. It's ideal for inference, fine-tuning, and experimentation where training speed is secondary to VRAM capacity. If speed matters more, upgrade to the NVIDIA RTX 4090 Server. For a cheaper option with less VRAM, see the NVIDIA RTX 3080 Server.