---
title: "AI Infrastructure Insights | Aguasto"
description: "Aguasto's analysis of dedicated compute, managed inference and the operating economics of future AI infrastructure."
canonical: "https://www.aguasto.com/insights"
last-updated: "2026-10-12"
---

# AI Infrastructure Insights | Aguasto

Canonical HTML: [Insights](https://www.aguasto.com/insights)

> Aguasto's analysis of dedicated compute, managed inference and the operating economics of future AI infrastructure.

[Resources](https://www.aguasto.com/resources) [GPU Library](https://www.aguasto.com/gpus) [Model Index](https://www.aguasto.com/models) [Inference Stack](https://www.aguasto.com/inference-stack) [Learn](https://www.aguasto.com/learn) [Insights](https://www.aguasto.com/insights) [Research](https://www.aguasto.com/research) [Engineering tools](https://www.aguasto.com/tools)

Aguasto / insights

## An operating perspective.

Aguasto analysis of compute economics and infrastructure decisions. Scenarios expose their assumptions; they do not promise investment returns or available service pricing.

Original Aguasto conceptual illustration. Not manufacturer geometry, an operating Aguasto asset, or a measured benchmark.

Aguasto Research documents third-party hardware, models and software. References do not represent Aguasto inventory, evaluated deployments or available inference services.

### Selected publications

Aguasto insights

#### Dedicated compute and shared inference: compare the whole workload

Provide a defensible cost-comparison method that includes idle reservation, completed tokens, operating scope and latency rather than a universal break-even claim.

Sources reviewed Oct 12, 2026

[Dedicated compute and shared inference: compare the whole workload](https://www.aguasto.com/insights/dedicated-and-shared-inference-economics)

## Company navigation

- [Home](https://www.aguasto.com/)
- [Infrastructure](https://www.aguasto.com/infrastructure)
- [GPU Cloud](https://www.aguasto.com/gpu-cloud)
- [AI Inference](https://www.aguasto.com/ai-inference)
- [Development & Investment](https://www.aguasto.com/development)
- [Company](https://www.aguasto.com/company)
- [Contact](https://www.aguasto.com/contact)
- [Privacy](https://www.aguasto.com/privacy)
- [Resources](https://www.aguasto.com/resources)
- [GPU Library](https://www.aguasto.com/gpus)
- [Model Index](https://www.aguasto.com/models)
- [Inference Stack](https://www.aguasto.com/inference-stack)
- [Learn](https://www.aguasto.com/learn)
- [Insights](https://www.aguasto.com/insights)
- [Research](https://www.aguasto.com/research)
- [Industry cases](https://www.aguasto.com/research/cases)
- [Why Modular](https://www.aguasto.com/why-modular)
- [Partners](https://www.aguasto.com/partners)
- [GPU comparison](https://www.aguasto.com/gpus/compare)
- [Model comparison](https://www.aguasto.com/models/compare)
- [Engineering tools](https://www.aguasto.com/tools)
- [Development friction](https://www.aguasto.com/research/hyperscale-development-friction)
- [NVIDIA H100 SXM](https://www.aguasto.com/gpus/h100)
- [NVIDIA H200 SXM](https://www.aguasto.com/gpus/h200)
- [NVIDIA B200 SXM](https://www.aguasto.com/gpus/b200)
- [NVIDIA B300](https://www.aguasto.com/gpus/b300)
- [NVIDIA GB200 NVL72](https://www.aguasto.com/gpus/gb200-nvl72)
- [NVIDIA GB300 NVL72](https://www.aguasto.com/gpus/gb300-nvl72)
- [NVIDIA Vera Rubin NVL72](https://www.aguasto.com/gpus/vera-rubin-nvl72)
- [AMD Instinct MI300X](https://www.aguasto.com/gpus/mi300x)
- [AMD Instinct MI325X](https://www.aguasto.com/gpus/mi325x)
- [AMD Instinct MI355X](https://www.aguasto.com/gpus/mi355x)
- [AMD Instinct MI455X](https://www.aguasto.com/gpus/mi455x)
- [AMD Helios](https://www.aguasto.com/gpus/helios)
- [GLM-4.5](https://www.aguasto.com/models/glm-4-5)
- [Qwen3-235B-A22B](https://www.aguasto.com/models/qwen3-235b-a22b)
- [DeepSeek-R1](https://www.aguasto.com/models/deepseek-r1)
- [Llama 3.3 70B Instruct](https://www.aguasto.com/models/llama-3-3-70b-instruct)
- [Gemma 3 27B IT](https://www.aguasto.com/models/gemma-3-27b-it)
- [gpt-oss-120b](https://www.aguasto.com/models/gpt-oss-120b)
- [Kimi-K2-Instruct](https://www.aguasto.com/models/kimi-k2-instruct)
- [vLLM](https://www.aguasto.com/inference-stack/vllm)
- [SGLang](https://www.aguasto.com/inference-stack/sglang)
- [TensorRT-LLM](https://www.aguasto.com/inference-stack/tensorrt-llm)
- [NVIDIA Dynamo](https://www.aguasto.com/inference-stack/dynamo)
- [NVIDIA Triton Inference Server](https://www.aguasto.com/inference-stack/triton)
- [AMD ROCm](https://www.aguasto.com/inference-stack/rocm)
- [Ray Serve](https://www.aguasto.com/inference-stack/ray-serve)
- [Kubernetes GPU orchestration — NVIDIA device plugin](https://www.aguasto.com/inference-stack/kubernetes)
- [Model weights are only the beginning of the memory budget](https://www.aguasto.com/learn/model-weights-and-runtime-memory)
- [Why tokens per second is not enough to benchmark inference](https://www.aguasto.com/research/inference-benchmark-methodology)
- [Prefill, decode and the cost of separating them](https://www.aguasto.com/learn/prefill-decode-and-disaggregated-serving)
- [Choosing between vLLM, SGLang and TensorRT-LLM](https://www.aguasto.com/learn/choosing-an-inference-serving-framework)
- [From Power to Inference—Building a Distributed AI Compute Network](https://www.aguasto.com/learn/from-power-to-inference)
- [Dedicated compute and shared inference: compare the whole workload](https://www.aguasto.com/insights/dedicated-and-shared-inference-economics)
- [Distributed inference reliability begins with the failure boundary](https://www.aguasto.com/learn/distributed-inference-reliability)
- [Core Scientific: reading contracted, energized and billed capacity](https://www.aguasto.com/research/cases/core-scientific-capacity-disclosures)
- [Why Modular AI Infrastructure Matters Now](https://www.aguasto.com/research/why-modular-ai-infrastructure-matters-now)
- [Official LinkedIn](https://www.linkedin.com/company/aguasto)

This is a generated representation of the public HTML page. Diagrams are conceptual. GPU and inference services are planned and are not currently available to book or call. The contact page describes the available inquiry flow.