Cost, Billing, and Ops
Latest articles in Cost, Billing, and Ops.
GPU Cluster Architecture: Compute, Network, Storage, and Control Plane
A practical GPU cluster architecture guide for compute nodes, network fabric, storage, Kubernetes or Slurm control plane, observability, and acceptance tests.
NVIDIA H20 vs H100: Inference, Memory, Availability, and Compliance
A practical H20 vs H100 comparison for enterprise AI teams, covering inference, memory, availability, export-control risk, and when H200 or model APIs are better baselines.
Best Cloud GPU Rental Platforms 2026: Price, Capacity, Network, and Support
A practical 2026 shortlist of GPU cloud platforms for AI teams, comparing price posture, capacity, network, support, and when a model API is the better baseline.
NVIDIA Blackwell Ultra B300: What Changed from B200?
A practical NVIDIA B300 Blackwell Ultra tracker for AI infrastructure teams comparing B300 specs, release status, price caveats, and workload fit against B200.
AMD MI455X and Helios: Architecture, Memory, and Availability Tracker
A buyer-focused tracker for AMD MI455X and Helios covering architecture, HBM4 memory, bandwidth, availability, vLLM readiness, provider questions, and model/API fallback strategy.
NVIDIA Vera Rubin GPU: GPU, NVL72, Memory, Networking, and Availability Tracker
A current tracker for NVIDIA Vera Rubin GPU specs, DGX Vera Rubin NVL72, HBM4 memory, networking, and availability milestones for cloud GPU buyers.
OpenAI Image API Pricing: GPT Image 2.5 Rates, Cost Formula, and Budget Controls
Learn how OpenAI image API pricing works for GPT Image 2.5, including token rates, cached input rules, partial images, Batch, and cost per accepted image.
GB200 vs B200: Grace Blackwell Superchip or x86 HGX?
Compare GB200 vs B200 for AI infrastructure procurement: Grace Blackwell rack-scale NVL72 systems, B200 HGX/x86 nodes, benchmarks, and TCO checks.
RoCE vs InfiniBand for GPU Clusters: Latency, Operations, and Cost
Compare RoCE and InfiniBand for multi-node GPU clusters with a practical decision matrix, NCCL acceptance test, cost model, and procurement checklist.
Serverless GPU vs Dedicated GPU: Cost, Cold Starts, and Control
Compare serverless GPU vs dedicated GPU by cost per accepted output, cold starts, idle capacity, autoscaling, and operational control.
AI Image Generation API Pricing Comparison: GPT Image, Gemini, Imagen, and fal
Compare image generation API pricing across GPT Image, Gemini Image, Imagen, and fal routes by normalizing billing units into cost per accepted image.
What Are the Hidden Costs of Cloud GPU Services? Storage, Egress, Idle Time, and Support
A practical cloud GPU TCO guide for finding storage, egress, idle time, failed-job, support, networking, and operations costs before the invoice arrives.
On-Demand vs Spot vs Reserved GPU Pricing: Which Model Fits Your Workload?
A workload-driven framework for choosing on-demand, spot, or reserved GPU capacity without confusing the listed hourly rate with completed workload cost.
AI GPU Selection Guide: Match Training and Inference Workloads to the Right GPU
A practical AI GPU selection guide for teams matching training, fine-tuning, LLM inference, media generation, and evaluation workloads to the right GPU and capacity model.
Private GPU Cloud: Architecture, Isolation, and Operating Model
Learn how to evaluate private GPU cloud architecture, isolation, scheduler ownership, security evidence, operating model, TCO, and acceptance tests.
vLLM Deployment Guide: Serve an OpenAI-Compatible LLM API on GPUs
Deploy vLLM as an OpenAI-compatible API on GPUs with Docker, RunPod Serverless, Ray Serve, metrics, rollout controls, and cost-per-accepted-output checks.
GPU Cloud vs Model API: When Self-Hosting Actually Saves Money
Compare GPU cloud vs model API economics with a break-even worksheet for accepted output cost, utilization, retries, idle capacity, and serving operations.
GPU Cluster TCO: Cloud Rental vs Colocation vs On-Premises
Compare GPU cluster TCO across cloud rental, colocation, and on-premises with a practical FinOps worksheet for AI infrastructure buyers.
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