DeployCue Cloud Cost Blog
Practical guides for developers and ML teams: how to choose a GPU host, cutting egress costs, LLM API pricing, spot vs on-demand, storage tiers, Kubernetes economics, and cloud billing explained.
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Together AI vs Fireworks AI: Inference Speed and Price Compared
Two leading open-model inference platforms, compared on speed, pricing, model selection, and where each one earns its keep.
Lambda Labs vs CoreWeave: Neocloud Heavyweights Compared
Two of the biggest GPU neoclouds, compared on pricing, scale, reservations, and which one fits training versus production serving.
RunPod vs Vast.ai: Which GPU Marketplace Is Cheaper?
Two popular GPU marketplaces, two very different models. Here is how RunPod and Vast.ai compare on price, reliability, and developer experience.
AWS vs GCP vs Azure GPU Pricing: Hyperscaler Showdown 2026
How the big three cloud providers price GPU instances, where each wins, and how to read past the sticker rate before you commit.
GPU Spot Price Volatility: How Much Rates Swing and Why
Spot GPU prices can swing sharply and reclaim capacity without warning. Here is what drives the volatility and how to build workloads that survive it.
Snapshot and Backup Storage Pricing in the Cloud, Demystified
Snapshots and backups quietly accumulate cost. Here is how incremental snapshot pricing works and how to keep your backup storage bill under control.
Prompt Caching and Pricing: How Cached Tokens Cut Your Bill
Prompt caching can slash the cost of repeated context. Here is how cached-token pricing works and how to structure prompts to capture the discount.
How GPU Memory Size Drives Cloud Pricing: VRAM Cost Curve
VRAM is often the real reason a GPU costs what it does. Here is how memory size shapes the cloud price curve and how to right-size for your model.
Speech-to-Text API Pricing: Cost Per Audio Hour Compared
How speech-to-text APIs price by audio hour, what features add to the rate, and how to estimate transcription costs at production scale.
GPU Cloud Billing Units: Per-Second, Per-Minute, and Per-Hour Compared
Billing granularity quietly shapes your GPU bill. Compare per-second, per-minute, and per-hour pricing and learn which fits your workload.
Vector Database Hosting Costs: Pricing the RAG Storage Layer
What drives vector database hosting costs in a RAG stack, from dimensions and vector count to index type, replicas, and query volume.
Image Generation API Pricing: Cost Per Image Across Providers
How image generation APIs price each render, from resolution and steps to quality tiers, and how to estimate your true cost per image at scale.
Reader favourites
Deploying Mixtral and MoE Models: Cost Quirks of Sparse Experts
Mixture-of-experts models like Mixtral are cheap to run but expensive to hold in memory. That quirk drives every cost decision.
Inference Autoscaling: Handling Traffic Spikes Without Overpaying
Autoscaling inference well means absorbing spikes without paying for idle GPUs the rest of the time. Here is how to tune it.
Continuous Batching: The Trick Behind High-Throughput LLM Serving
Continuous batching keeps the GPU busy by swapping finished requests for new ones mid-flight. It is why modern serving is so efficient.
AWS Trainium vs NVIDIA GPUs: Custom Silicon for Training Compared
AWS Trainium promises lower training costs than NVIDIA GPUs, but the tradeoff is ecosystem maturity. Here is how the two compare for real workloads.
GPU Cloud Billing Units: Per-Second, Per-Minute, and Per-Hour Compared
Billing granularity quietly shapes your GPU bill. Compare per-second, per-minute, and per-hour pricing and learn which fits your workload.
Cost Per Million Tokens Compared Across Top Inference APIs
How to compare cost per million tokens across inference APIs the right way, accounting for input and output splits, model tiers, and hidden fees.
Set Up GPU Monitoring With Prometheus and Grafana
Build a GPU monitoring dashboard with Prometheus and Grafana so you can spot idle GPUs, thermal throttling, and wasted spend at a glance.
Set Up a Fault-Tolerant Spot Training Job From Scratch
Build a training job that survives spot interruptions through checkpointing, automatic resume, and a sensible fallback.
Setting Up GPU Cloud Budget Alerts Before Bills Explode
A beginner-friendly guide to GPU cloud budget alerts: thresholds, anomaly detection, and hard stops that catch runaway spend before it hurts.
GPU Cloud Marketplaces: How Spot GPU Bidding Actually Works
How GPU cloud marketplaces and spot bidding work: where the cheap capacity comes from, the interruption risk, and how to use it safely.
GPU Sizing for LLM Serving: Matching VRAM to Model Size
Pick a GPU too small and the model will not load; too big and you overpay. Here is how to size VRAM to your model.
Batch Inference: How Async Processing Slashes Token Costs
If your workload can wait minutes or hours, batch inference can cut token costs sharply. Here is when and how to use it.