Admin: New server config article

2026-04-12T15:39:31Z

New server config article

New page

'''NVIDIA A100 Server''' is a professional AI/ML GPU cloud server available from [https://en.immers.cloud/signup/r/20241007-8310688-334/ Immers Cloud]. The A100 remains the industry standard for many ML workloads, offering 80 GB HBM2e memory and proven reliability at a lower price point than the newer H100.

== Specifications ==
{| class="wikitable"
|-
! Component !! Specification
|-
| '''GPU''' || NVIDIA A100 SXM (Ampere architecture)
|-
| '''VRAM''' || 80 GB HBM2e
|-
| '''Memory Bandwidth''' || 2.0 TB/s
|-
| '''FP16 Performance''' || ~312 TFLOPS
|-
| '''TF32 Performance''' || ~156 TFLOPS
|-
| '''Interconnect''' || NVLink 3.0 (600 GB/s)
|-
| '''Starting Price''' || From $2.37/hr
|}

== Performance ==
The A100 has been the backbone of AI infrastructure since 2020 and continues to be highly relevant:
* '''80 GB HBM2e''' — same VRAM as the H100, enough for most models
* '''3rd-gen Tensor Cores''' with TF32, FP16, BF16, and INT8 support
* '''Multi-Instance GPU (MIG)''' — partition one A100 into up to 7 isolated instances
* '''2.0 TB/s memory bandwidth''' — sufficient for most training and inference workloads

The A100 costs '''38% less per hour''' than the [[NVIDIA H100 Server]] ($2.37 vs $3.83). For workloads that don't benefit from FP8 or the Transformer Engine, the A100 provides nearly equivalent results at lower cost.

For inference specifically, the A100 often provides better cost-efficiency than the H100 when serving models that fit within the FP16/INT8 precision range.

== Best Use Cases ==
* Cost-effective AI model training (7B–30B parameters)
* Production inference serving at scale
* Fine-tuning with LoRA/QLoRA
* Computer vision (image classification, object detection, segmentation)
* Natural language processing and text generation
* Multi-instance GPU sharing for multiple small models
* Scientific computing (molecular dynamics, climate modeling)

== Pros and Cons ==
=== Advantages ===
* Proven, mature platform with years of production use
* 80 GB VRAM handles large models
* Multi-Instance GPU (MIG) for efficient resource sharing
* 38% cheaper than H100 per hour
* Excellent software ecosystem and community support
* Wide framework compatibility (PyTorch, TensorFlow, JAX)

=== Limitations ===
* No FP8 support (H100 feature)
* No Transformer Engine
* Lower memory bandwidth than H100 (2.0 vs 3.35 TB/s)
* Previous generation — eventually will be phased out
* NVLink 3.0 (600 GB/s) vs H100's NVLink 4.0 (900 GB/s)

== Pricing ==
Available from [https://en.immers.cloud/signup/r/20241007-8310688-334/ Immers Cloud] starting at '''$2.37/hr'''. One of the best value propositions for professional-grade AI compute. Monthly cost for 24/7 usage: approximately $1,706.

== Recommendation ==
The '''NVIDIA A100 Server''' is the smart choice for teams that want professional-grade AI compute without paying H100 premium pricing. If your training workloads are in the 7B–30B parameter range, or you're doing inference serving, the A100 delivers excellent results at 38% lower hourly cost. Only upgrade to the [[NVIDIA H100 Server]] if you need FP8 training, Transformer Engine, or higher memory bandwidth.

== See Also ==
* [[NVIDIA H100 Server]]
* [[NVIDIA V100 Server]]
* [[NVIDIA RTX 4090 Server]]
* [[NVIDIA RTX A5000 Server]]

[[Category:GPU Servers]]
[[Category:AI Training]]
[[Category:Data Center GPU]]

NVIDIA A100 Server - Revision history

Admin: New server config article