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NVIDIA RTX 3080 Server
NVIDIA RTX 3080 Server is a budget GPU cloud server available from Immers Cloud. At $0.48/hr with 10 GB GDDR6X, the RTX 3080 is one of the most affordable GPU options for basic ML and rendering workloads.
Specifications
| Component | Specification |
|---|---|
| GPU | NVIDIA GeForce RTX 3080 (Ampere architecture) |
| VRAM | 10 GB GDDR6X |
| CUDA Cores | 8,704 |
| Memory Bandwidth | 760 GB/s |
| Tensor Cores | 3rd Generation |
| TDP | 320W |
| Starting Price | From $0.48/hr |
Performance
The RTX 3080 delivers solid Ampere-generation compute at a budget price:
- 8,704 CUDA cores — about 83% of the RTX 3090
- 10 GB GDDR6X — the main limitation for ML workloads
- 3rd-gen Tensor Cores for accelerated training and inference
- 760 GB/s bandwidth — adequate for most inference tasks
The 10 GB VRAM is the key constraint. While compute performance is close to the RTX 3090, many modern models require more than 10 GB. This limits the RTX 3080 to:
- Smaller models (up to ~3B parameters in FP16)
- Quantized inference of 7B models (tight fit)
- Image generation at lower resolutions or with optimizations
Best Use Cases
- Small model training (up to 3B parameters)
- Inference of quantized models
- AI image generation at standard resolutions
- Computer vision inference (YOLO, ResNet)
- 3D rendering and visualization
- Entry-level ML learning and experimentation
- Video encoding with NVENC
Pros and Cons
Advantages
- $0.48/hr — extremely affordable GPU compute
- Ampere Tensor Cores for ML acceleration
- Good compute-per-dollar for workloads that fit in 10 GB
- Solid for inference of smaller models
- Low entry barrier for GPU experimentation
Limitations
- Only 10 GB VRAM — severely limits model size
- Cannot run most modern LLMs without heavy quantization
- No ECC or NVLink
- VRAM limitation makes many workloads impossible
- May need to rent a bigger GPU anyway
Pricing
Available from Immers Cloud starting at $0.48/hr. Monthly cost for 24/7: approximately $346.
Recommendation
The NVIDIA RTX 3080 Server is best for users with workloads that definitely fit within 10 GB VRAM — small model inference, computer vision, rendering, and experimentation. If there's any chance you'll need more VRAM, skip to the NVIDIA RTX 3090 Server ($0.75/hr) for 24 GB. The small price difference is almost always worth the 14 GB VRAM upgrade.