Practical guides and real cost breakdowns for running Claude Code and Codex: per-model pricing, open-weight models like GLM 5.2, budgets, and governance.
Most coding-agent work is routine and doesn't need your priciest model. Smart routing serves the cheapest capable model per request, so you pay top rates only when the work needs it. One switch, no tuning.
Three levers do the work: see who spends what, set hard-stop budgets, and control which model runs. Plus how token compression cut our own bill 70%.
Set daily or weekly caps in dollars, tokens, or sessions, per user and per project. Hard stops block spend before it goes over, and alerts warn you first.
See live cost per developer and per project by tagging every request to a user and a project. Stop guessing at one big bill, and charge costs back to the right team.
A forgotten agent loop or a leaked key can drain a budget quietly. Hard caps that block at the limit, plus spend-spike alerts and abuse detection, catch it early.
LiteLLM is a free, open-source gateway you run yourself. Clawgate is a managed tool built for governing Claude Code and Codex. An honest look at when each one wins.
The same coding task cost 26¢ on one model and over $3 on another, about a 12× spread. How to match the model to the job and route work to the cheapest capable one.
AI coding agents resend bulky context every turn, and you pay for it each time. Compression cuts up to 92% of those tokens while accuracy holds. Here's how it works.
Route Claude Code through a gateway that holds the Bedrock access, so developers get AI without direct AWS keys, and every request has a per-user budget.
Give your team AI while keeping spend under control: budgets, per-project tracking, model control, and abuse alerts in one dashboard, at fair pass-through pricing.
Clawgate, LiteLLM, Portkey, Helicone, and the built-in Anthropic/OpenAI limits — compared honestly on hard-stop budgets, per-developer cost tracking, setup effort, and pricing, including where each competitor is the better pick.
Uber burned its 2026 AI budget in four months. Meta's staff used 73.7 trillion tokens in 30 days. The speed is real — so is the cost. What goes wrong, and how a control layer keeps both.
One prompt, six top models, one fair comparison. The cheapest run cost 26¢, the priciest over $3 — a 12× spread for the same task. Here's how to see real per-model cost and stop overpaying.
A step-by-step guide to running GLM 5.2 — an open-weight model near Opus benchmarks at a fraction of the cost — inside Claude Code and Codex, with one key, dashboard model control, and automatic usage tracking.
Give your team the AI they need. Give yourself the visibility and control you need.
