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<p><b>New page</b></p><div>'''NVIDIA RTX 5090 Server''' is a latest-generation consumer GPU cloud server available from [https://en.immers.cloud/signup/r/20241007-8310688-334/ Immers Cloud]. The RTX 5090 is NVIDIA's flagship Blackwell consumer GPU with 32 GB GDDR7 memory and 21,760 CUDA cores.<br />
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== Specifications ==<br />
{| class="wikitable"<br />
|-<br />
! Component !! Specification<br />
|-<br />
| '''GPU''' || NVIDIA GeForce RTX 5090 (Blackwell architecture)<br />
|-<br />
| '''VRAM''' || 32 GB GDDR7<br />
|-<br />
| '''CUDA Cores''' || 21,760<br />
|-<br />
| '''Memory Bandwidth''' || ~1,792 GB/s<br />
|-<br />
| '''Architecture''' || Blackwell (5th gen)<br />
|-<br />
| '''Tensor Cores''' || 5th Generation<br />
|-<br />
| '''Starting Price''' || From $1.46/hr<br />
|}<br />
<br />
== Performance ==<br />
The RTX 5090 brings NVIDIA's latest Blackwell architecture to the consumer tier:<br />
* '''32 GB GDDR7''' — highest VRAM on any consumer GPU, matching the V100<br />
* '''21,760 CUDA cores''' — 33% more than the RTX 4090's 16,384<br />
* '''5th-gen Tensor Cores''' with FP4 support for next-gen inference<br />
* '''GDDR7 memory''' — new memory technology with higher bandwidth and lower power<br />
<br />
Compared to the [[NVIDIA RTX 4090 Server]] ($0.93/hr):<br />
* ~50–70% faster for ML training and inference<br />
* 33% more VRAM (32 GB vs 24 GB)<br />
* 57% higher hourly cost<br />
* Better cost-efficiency for workloads that benefit from larger VRAM<br />
<br />
Compared to data center GPUs, the RTX 5090 trades ECC memory and NVLink for much lower cost. For single-GPU workloads, it can rival the [[NVIDIA A100 Server]] in raw throughput at 38% lower hourly cost.<br />
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== Best Use Cases ==<br />
* ML model training (up to 13B parameters)<br />
* AI inference with latest Blackwell optimizations<br />
* Stable Diffusion, Flux, and AI image generation<br />
* Video AI processing (upscaling, frame interpolation)<br />
* 3D rendering (Blender, Unreal Engine)<br />
* LLM inference with 4-bit quantization (up to 30B models)<br />
* Real-time AI applications<br />
<br />
== Pros and Cons ==<br />
=== Advantages ===<br />
* 32 GB GDDR7 — most VRAM on consumer GPU<br />
* Latest Blackwell architecture with FP4 tensor cores<br />
* 21,760 CUDA cores for massive parallel compute<br />
* $1.46/hr — much cheaper than data center GPUs<br />
* Excellent for single-GPU workloads<br />
<br />
=== Limitations ===<br />
* No ECC memory (consumer GDDR7)<br />
* No NVLink for multi-GPU communication<br />
* Consumer-grade — may have lower sustained reliability<br />
* GDDR7 bandwidth lower than HBM on data center GPUs<br />
* Newer architecture — driver and framework support still maturing<br />
<br />
== Pricing ==<br />
Available from [https://en.immers.cloud/signup/r/20241007-8310688-334/ Immers Cloud] starting at '''$1.46/hr'''. Monthly cost for 24/7: approximately $1,051.<br />
<br />
== Recommendation ==<br />
The '''NVIDIA RTX 5090 Server''' is the cutting-edge consumer GPU choice. At $1.46/hr with 32 GB VRAM and Blackwell architecture, it offers outstanding performance per dollar for single-GPU ML workloads. Choose this over the [[NVIDIA RTX 4090 Server]] if you need more VRAM or latest architecture features. For multi-GPU training or ECC reliability, choose data center GPUs like the [[NVIDIA A100 Server]].<br />
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== See Also ==<br />
* [[NVIDIA RTX 4090 Server]]<br />
* [[NVIDIA A100 Server]]<br />
* [[NVIDIA H100 Server]]<br />
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[[Category:GPU Servers]]<br />
[[Category:Consumer GPU]]<br />
[[Category:AI Training]]</div>Admin