Every major agent — Claude Code, Cursor, Copilot, Codex, Gemini CLI, Aider, Cline, Windsurf, opencode — priced and explained. What drives the cost, what each tool charges, and the practical way to cut your token bill 40–70%.
AI coding agents start at $10–$20/month per developer, but real cost is driven by token usage: active professionals commonly spend $150–$400/month. You cut it by compressing prompts and CLI output, killing redundant context, caching repeated context, and right-sizing the model — techniques that reduce token bills 40–70%.
Almost every AI coding agent bills on tokens — directly through an API, or indirectly through a subscription's credit or compute allowance. Understanding what actually consumes those tokens is the difference between a $60 month and a $400 one. Your typed prompts are rarely the main cost. Five things are.
Agentic sessions are multi-turn. On every turn, the entire conversation so far — prompts, tool results, file contents, prior reasoning — is re-sent as input. A session that starts at 5K tokens can be re-sending 150K+ tokens per turn by the end. You pay for that growing history again and again unless it is cached or compacted.
To edit code, an agent must see it. Some tools send a compact repo map (efficient); others read whole files into context (expensive). Large files, generated code, lockfiles, and vendored dependencies can dump tens of thousands of tokens into a single turn — most of which the model never needed.
In a typical session, roughly a third of file reads are duplicates — the agent loads the same file three to five times because it lost track of what it already had. Each duplicate re-bills the file's full token count on input. This is one of the largest and least-visible sources of waste.
Filler words, hedging, politeness padding, and duplicated instructions inflate every prompt. Worse, terminal agents pipe raw CLI output — file listings, test logs, stack traces — straight into context. A single verbose command can add 10K–150K tokens of noise the model has to read and re-read.
Output tokens cost 4–5× more than input on frontier models. When an agent generates long explanations, full-file rewrites, or verbose diffs, output cost dominates. Using a top-tier reasoning model for tasks a cheaper model could handle multiplies this — often the single biggest lever on a monthly bill.
Long sessions without a summarize-and-reset step let context balloon toward the model's limit. Every subsequent turn then re-sends a near-maximal context. Proactive compaction — summarizing at 60–70% capacity — keeps per-turn cost flat instead of compounding.
The takeaway: cost is a function of how much context flows through the model each turn, not how much you type. For the mechanics of measuring and reducing that flow, see what token optimization is and how to reduce AI API costs.
The major AI coding agents at a glance — starting price, how billing works, and a note on token efficiency. Prices are the entry point as of July 2026; open-source clients are free to run and you pay only for the model tokens you use. Each tool links to its dedicated Terse guide.
| Tool | Starting price | Billing model | Token-efficiency note |
|---|---|---|---|
| Claude Code | $20/mo | Sub with rolling limits; API-direct beyond | Very efficient — prompt caching + proactive /compact |
| Cursor | $20/mo Pro | Monthly credit pool; overage billed | Agent mode can drain credits on large tasks |
| GitHub Copilot | Free / $10 Pro | Usage-based AI Credits (since June 2026) | Flat fee hides premium-model credit burn |
| Codex CLI (OpenAI) | Sub or API | ChatGPT/Codex subscription or OpenAI API | Heavy API runs add up fast on GPT-5.x |
| Gemini CLI (Google) | Free tier | Large free tier; API-billed beyond | 1M context is cheap to fill — watch big reads |
| Aider | Free + tokens | Open-source; pay only model tokens | Efficient by design — compact repo map |
| Cline | Free (BYOM) | Open-source; your own API key | You control model + cost; Plan/Act review gate |
| Windsurf | Free / credits | Free tier; credit-based paid (Cascade) | Agent-forward flow burns credits when leaned on |
| opencode | Free + tokens | Open-source (MIT); pay model tokens | Provider-agnostic; cost = whichever model you pick |
"Free" for open-source clients refers to the software, not the model. Pricing and availability change often — check each vendor before committing. Terse works alongside all nine and reduces token usage on every one.
How to read this table. A low sticker price does not mean a low bill. Subscriptions like Cursor and Copilot include an allowance; exceed it, or reach for premium models, and you pay per credit or per token on top. API-direct tools (Codex CLI, Claude Code beyond its plan, BYOM clients) have no ceiling — cost tracks usage exactly. That is why two developers on the "same" $20 plan can see a 5× difference in real spend. The controllable variable is always token throughput, covered next.
For per-token math, real monthly estimates by usage tier, and where the tokens actually go, read the dedicated pricing breakdowns.
Choosing between two agents, or looking to switch? These side-by-side breakdowns weigh capability, price, and token efficiency.
Four techniques, ordered by impact per hour of effort. Each works on every agent above, because they all bill on the same underlying commodity — tokens. Terse automates all four on-device, so nothing leaves your machine.
Strip filler, fix typos, remove redundancy, and shrink CLI noise before it reaches the context window. Terse runs a multi-stage on-device pipeline: spell correction, NLP analysis, telegraph compression, and pattern optimization. Average 40–70% reduction on prompts, up to 89% on CLI output.
Highest ImpactRoughly a third of file reads in a session are duplicates. Terse's selective context engine flags files already in context and interrupts duplicate reads before they re-bill, so the model never pays twice for the same file.
Silent SavingsYou cannot cut what you cannot see. Terse's Agent Monitor shows the token cost of every turn in real time, so you catch the expensive turns — a giant file read, an unnecessary Opus call — before they compound across a session. Estimate your own with the token calculator.
VisibilityOutput tokens cost 4–5× more on frontier models, and simple edits rarely need one. Route boilerplate, searches, and mechanical edits to a cheaper model and reserve the frontier tier for genuine reasoning. Terse surfaces which turns are expensive so you can switch deliberately.
4–5× Cheaper for Simple TasksTwo more levers stack on top: enable prompt caching so repeated context (system prompt, project overview) costs ~90% less after the first turn, and compact proactively at 60–70% of the context limit so long sessions do not re-send a near-maximal context every turn. Together with the four techniques above, these are how disciplined teams turn a $400 month into a $120 one.
Terse compresses prompts and CLI output on-device before they hit the context window, catches duplicate file reads, and tracks per-turn cost. It is tool-agnostic by design, so it works alongside Claude Code, Cursor, Copilot, Codex CLI, Gemini CLI, Aider, Cline, Windsurf, and opencode. Estimate what you would save:
The most common questions about what AI coding agents cost in 2026 and how to spend less.
Terse compresses prompts, catches duplicate tool calls, and tracks per-turn cost — on-device, alongside every agent on this page. 30-day free trial, no credit card until it ends.