Codex Usage Limits and Credits: How the System Works
Codex limits are moving from plan allowances to token credits, and the exact numbers shift constantly. Here are the mechanics that stay true, and how to budget agent work across them.
By Kylian Migot · Updated August 2026 · 7 min read
Quick answer
Codex access comes through ChatGPT plans with usage allowances, moving to token-credit-based billing in 2026: work consumes credits by model and volume. Cloud tasks and the local CLI draw on the same plan, heavier tiers burn faster, and the best lever is tier routing, Terra by default, Sol where it pays, Luna for mechanical work.
Access
Via ChatGPT plans; cloud tasks and local CLI share one allowance
The meter
Moving to token credits in 2026, consumed by model and volume
Burn rate
Scales with tier; Sol fastest, Terra middle, Luna slowest
Community read
The $20 tier's Codex allowance is widely considered generous
Exact numbers
Change often, check OpenAI's Codex pricing docs for current terms
01
The Stable Mechanics
Codex metering has changed shape more than once, plan-based allowances, then a shift toward token credits, and pages that lead with specific quota figures go stale fast. What has stayed stable is the architecture underneath, and it is what you need to plan around.
Access rides on ChatGPT plans
Codex is included with paid ChatGPT plans, each carrying a usage allowance that scales with the tier. You are not buying a separate Codex subscription; you are spending an allowance attached to the plan you already have.
Token credits are the 2026 direction
Billing is moving to a token-credit system: work consumes credits in proportion to the model used and the tokens processed, and extra credits can be purchased beyond the plan's allowance. Metering by what work actually costs, rather than counting tasks or messages.
One plan across every surface
Cloud tasks kicked off from the web or IDE and local Codex CLI sessions draw on the same allowance. Delegating to the cloud moves the compute, not the bill, there is no separate cloud budget to arbitrage.
Heavier tiers burn faster
Credit consumption scales with the model tier: a Sol session costs meaningfully more of your allowance than the same work on Terra or Luna. Under credit billing, model choice is a spend decision, not just a quality one.
One data point worth having, attributed as what it is: community sentiment across dev forums has generally rated Codex allowances at the $20 tier as generous, with many engineers reporting moderate daily use rarely hits the ceiling. That is a sentiment about a moving target, not a spec, but it is consistent enough to be worth knowing.
Your AI workspace for shipping software.
Download AIDEN free and point it at your existing Claude Code or Codex setup. No credit card, running in minutes.
Free to start · macOS 12+ · No credit card required
02
Tier Burn Rates: The Price Ratio Is the Proxy
OpenAI's API token prices are the honest public proxy for how fast each tier consumes credits, they track what each model costs to run. The ratios are the point: routing a session from Sol down to Terra materially reduces its burn, and down to Luna cuts it by an order of magnitude.
Model
API price (burn proxy)
Relative burn
Route here
GPT-5.6 Luna
$0.2 in / $1.2 out per MTok
1x input / 1x output (baseline)
Quick mechanical edits, high-volume cheap tasks
GPT-5.6 Terra
$2 in / $12 out per MTok
10x input / 10x output
The default for routine implementation
GPT-5.6 Sol
$4 in / $20 out per MTok
20x input / 16.7x output
Hard terminal-agent work, ultra mode, long tool chains
Prices verified against vendor docs on August 29, 2026. Which tier earns its burn for which task shape, including when Sol's ultra mode justifies the premium, is covered in the best Codex model and the head-to-head Sol vs Terra vs Luna.
03
Three Strategies for Budgeting Codex Work
Treat the allowance as a budget and the levers become clear. Three of them do most of the work.
1. Route tiers by task
Terra as the default, Sol only where the task genuinely needs the top tier, Luna for mechanical high-volume work. Under credit billing this is the single biggest lever on how long an allowance lasts. Decision rules in best Codex model.
2. Add a second pool
A Claude plan is an independent budget, its limits never touch OpenAI's. Engineers who run both CLIs route work across two pools and hit ceilings far less often; AIDEN runs both on one board, which keeps the routing visible. The workflow is in Claude Code and Codex together.
3. Know when the API wins
Plan credits suit steady daily use. Per-token API billing wins at the extremes: bursty occasional use that never justifies a monthly fee, or sustained automation where an uncapped, deliberately budgeted per-token spend beats bouncing off plan ceilings.
QUESTIONS
FAQ
Do Codex cloud tasks and the local CLI share the same limits?
Yes. Cloud tasks delegated from the web or IDE and sessions run through the local Codex CLI draw on the same ChatGPT plan allowance. Offloading work to the cloud changes where it runs, not whose budget it spends. One plan, one budget, across every surface.
What are Codex credits?
Credits are OpenAI's token-based unit for metering Codex work, the model the system is moving to for 2026 billing. Work consumes credits in proportion to the model used and the volume of tokens processed, so a long Sol session costs meaningfully more credits than the same session on Terra or Luna. Plans include an allowance, and additional credits can be purchased when you need more.
Which Codex model burns through limits fastest?
Heavier tiers burn faster, and API token prices are the best public proxy for the ratio. GPT-5.6 Sol ($4 in / $20 out per MTok) is the fastest burn of the current family, above Terra ($2 in / $12 out per MTok), which in turn costs 10x Luna ($0.2 in / $1.2 out per MTok) on both input and output. Defaulting to Terra and reserving Sol for genuinely hard work is the biggest single lever on how far an allowance goes.
Is the $20 ChatGPT plan enough for Codex?
Community sentiment, and it is sentiment, not a guarantee, has generally rated Codex allowances at the $20 tier as generous relative to competitors, with many engineers reporting they rarely hit the ceiling on moderate daily use. Heavy parallel agent use is a different feature on any plan. Exact allowances change, so check OpenAI's official Codex pricing docs for current terms.
Should I use plan credits or API billing for Codex?
Plan credits win for steady, predictable daily use: a flat monthly cost with a known allowance. Per-token API billing wins at the extremes, occasional bursty use that never justifies a subscription, or sustained heavy automation where you would rather budget an uncapped per-token spend than repeatedly hit plan ceilings. Most individual engineers land on a plan; most CI-style automation lands on the API.
AIDEN runs your Codex CLI sessions as cards on a board, with the model tier chosen per feature, so Sol goes only where Terra can't. Free for one project.
