https://serverrental.store/index.php?action=history&feed=atom&title=NVIDIA_RTX_3090_ServerNVIDIA RTX 3090 Server - Revision history2026-04-14T21:47:47ZRevision history for this page on the wikiMediaWiki 1.36.1https://serverrental.store/index.php?title=NVIDIA_RTX_3090_Server&diff=5707&oldid=prevAdmin: New server config article2026-04-12T15:42:07Z<p>New server config article</p>
<p><b>New page</b></p><div>'''NVIDIA RTX 3090 Server''' is a value-oriented GPU cloud server available from [https://en.immers.cloud/signup/r/20241007-8310688-334/ 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.<br />
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== Specifications ==<br />
{| class="wikitable"<br />
|-<br />
! Component !! Specification<br />
|-<br />
| '''GPU''' || NVIDIA GeForce RTX 3090 (Ampere architecture)<br />
|-<br />
| '''VRAM''' || 24 GB GDDR6X<br />
|-<br />
| '''CUDA Cores''' || 10,496<br />
|-<br />
| '''Memory Bandwidth''' || 936 GB/s<br />
|-<br />
| '''Tensor Cores''' || 3rd Generation<br />
|-<br />
| '''TDP''' || 350W<br />
|-<br />
| '''Starting Price''' || From $0.75/hr<br />
|}<br />
<br />
== Performance ==<br />
The RTX 3090 remains highly relevant thanks to its 24 GB VRAM at an affordable price:<br />
* '''24 GB GDDR6X''' — same VRAM capacity as RTX 4090, enough for most models<br />
* '''10,496 CUDA cores''' with Ampere architecture<br />
* '''3rd-gen Tensor Cores''' — FP16, BF16, TF32, INT8 support<br />
* '''936 GB/s bandwidth''' — close to the RTX 4090's 1,008 GB/s<br />
<br />
Compared to the [[NVIDIA RTX 4090 Server]] ($0.93/hr):<br />
* ~50% slower for raw compute<br />
* Same 24 GB VRAM capacity<br />
* 19% cheaper per hour<br />
* Better value when VRAM matters more than speed<br />
<br />
For many inference workloads, the RTX 3090 performs similarly to the 4090 since inference is often memory-bound rather than compute-bound.<br />
<br />
== Best Use Cases ==<br />
* Budget ML training and fine-tuning<br />
* LLM inference with quantization<br />
* AI image generation (Stable Diffusion, Flux)<br />
* VRAM-hungry workloads on a budget<br />
* Computer vision model training<br />
* ML prototyping and experimentation<br />
* Video upscaling and AI enhancement<br />
<br />
== Pros and Cons ==<br />
=== Advantages ===<br />
* $0.75/hr — very affordable for 24 GB VRAM<br />
* Same VRAM capacity as RTX 4090<br />
* Ampere Tensor Cores for accelerated ML<br />
* Good bandwidth for inference workloads<br />
* Proven platform with mature driver support<br />
<br />
=== Limitations ===<br />
* ~50% slower compute than RTX 4090<br />
* Previous-gen Ampere architecture (no FP8)<br />
* No ECC memory or NVLink<br />
* Higher power consumption relative to performance<br />
* 350W TDP<br />
<br />
== Pricing ==<br />
Available from [https://en.immers.cloud/signup/r/20241007-8310688-334/ Immers Cloud] starting at '''$0.75/hr'''. Monthly cost for 24/7: approximately $540.<br />
<br />
== Recommendation ==<br />
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]].<br />
<br />
== See Also ==<br />
* [[NVIDIA RTX 4090 Server]]<br />
* [[NVIDIA RTX 3080 Server]]<br />
* [[NVIDIA RTX 2080 Ti Server]]<br />
<br />
[[Category:GPU Servers]]<br />
[[Category:Consumer GPU]]<br />
[[Category:Budget GPU]]</div>Admin