
Token Economics Across Traffic Profiles on Dedicated GPUs | DigitalOcean
Learn how LLM inference cost scales across traffic profiles on dedicated GPUs. Understand cost per token, GPU utilization, and batch sizing. Read the full br…
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Learn how LLM inference cost scales across traffic profiles on dedicated GPUs. Understand cost per token, GPU utilization, and batch sizing. Read the full br…

How prompt caching works, what each provider charges, and when it actually cuts LLM costs. A measured decision framework with real numbers from an H200 GPU D…

Which inference APIs are truly drop-in OpenAI replacements in 2026? Verified pricing, real benchmarks, and what breaks when you switch providers.

What long-context LLM requests really cost: KV cache math, latency, per-session pricing, and when RAG still wins.

How production teams route LLM traffic across model tiers and providers: a measured 36× cost spread, LiteLLM vs OpenRouter vs first-party routing, and failover.

Bursty LLM traffic leaves a dedicated GPU billing through idle hours. See the sustained floor math, the utilization crossover, and when serverless stays chea…

A practical framework for deciding which parts of an AI workload to run on local hardware and which to run on DigitalOcean serverless inference — with a work…

Learn how server-side tools work in AI agents, how they affect architecture and latency, and when it makes sense to move from client-side tool execution to a…

Learn how to use DigitalOcean’s Inference Router to govern multi-model API costs, route requests by task complexity, and reduce LLM inference spend.

In this article we learn how to build an application with real users using DigitalOcean.

Why the same LLM can behave like a completely different product depending on which serverless inference provider you use, and how to benchmark before you com…

A firsthand build log showing how DigitalOcean’s Inference Router drove 596 agentic coding tasks to complete a full Godot game for about $8.25 — versus an es…

A Private Droplet has no public network interface, so you can’t SSH to it directly. The standard way in is a bastion host (jump host): a small Droplet wi…

Serverless LLM inference has no single performance metric that can reflect performance for all applications. Throughput, latency, reliability, and cost each …

Upload case files to Spaces, index with Knowledge Bases, retrieve via MCP, and deploy a LegalTech FastAPI RAG app using Serverless Inference.
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