Normalize the comparison
An AI coding price table often puts a monthly editor seat next to a token rate and a free extension. Those numbers are not comparable units. Choose a workload first: for example, twenty small questions, eight tested patches and two difficult migrations per month. Specify the model quality required and whether a local model is acceptable. Then estimate each option's fixed charges, included use and variable cost for that same workload. If one product cannot perform a required workflow, a low price does not make it a bargain.
Subscription products bundle different things
Cursor sells an editor experience with included model allowances and possible on-demand use. Claude Code and Codex can be available through eligible account plans, with usage limits and product-specific rules. The subscription may include value unrelated to coding, or its coding capacity may be shared with other activity. Read each live pricing page and dashboard rather than assuming a $20 plan from two vendors buys the same resource. Features, review interface and model route also affect how much work one paid session can accomplish.
BYOK separates the workspace and model bills
Cline's individual extension is free, while provider inference is billed separately unless a local model is used. Licuse's BYOK workspace is free with model charges at OpenRouter, OpenAI or Anthropic. Cursor also supports custom keys under its own rules. BYOK can be attractive for intermittent work or existing provider budgets, but it is not a promise of free AI. Check whether the editor still has a seat fee, whether a router adds charges, and whether provider budgets are shared across tools.
Local inference changes the cost shape
Running a local model can avoid per-token cloud charges, yet the workstation, electricity, setup time and potential quality difference matter. A model that cannot reliably navigate your codebase may require more human repair. Cline supports local-model routes such as Ollama; Licuse currently does not offer offline inference. Compare local and remote options on the same repository tasks and hardware. The relevant question is not only the electricity cost per hour, but whether the model can produce a reviewable, tested patch.
Count retries and review
The true unit of output is a correct change you can merge, not a chat response. Record how many attempts a tool needs and whether it runs the right checks. A model that is cheaper per token but fails twice may cost more than a stronger model that succeeds once. Human review is necessary with all tools, but one workflow may make diffs, tests and command permissions easier to inspect. Treat that review experience as part of total cost because developer time is scarce.
Build a simple worksheet
Use columns for fixed monthly fee, included usage, expected provider tokens, routing fees, overage, local hardware and observed completion rate. Keep uncertain values as ranges. For each task class, estimate how many attempts and how much manual repair occurred in a trial. Do not present a precise monthly winner from invented token numbers. If the cost ranges overlap, choose on workflow quality, privacy and compatibility, then monitor real invoices during the first month.
Recheck the market
Model prices, subscriptions and plan allowances change. A comparison should state when it was checked and link directly to vendor documentation. Before purchase, verify the current terms for your region, account type and payment cycle. Price should guide an experiment, not replace it. A week of your own tasks, reviewed diffs and billing data will tell you far more than a universal ranking of assistants from cheapest to most expensive.
Compare the cost of verified tasks completed, not the list price alone.
Sources & further reading
References support the concepts and product descriptions discussed above. Features, prices and account eligibility can change; check the live documentation. Inclusion here is not a hands-on test or vendor endorsement.