DEV Community: StackVersus

Which AI coding plans let buyers count what they get

StackVersus — Mon, 02 Nov 2026 10:09:23 +0000

AI coding plans now share price points, mostly $20, $100 and $200 a month, but not a unit of measure. Claude uses time windows, Cursor uses a weekly pool, Copilot uses credits worth a cent, Kiro uses its own credits, Bolt uses tokens, Lovable uses credits, and Augment uses dollars. Only the last group lets a buyer divide price by quantity. The others publish multiples of a base they never quantify, or ranges wide enough to be hard to plan around. The thesis of this analysis is that the metering unit matters more than the sticker price, because it decides whether a buyer can check a plan before paying. Even the countable plans leave a second variable, the cost per unit, that the buyer has to work out.

Every figure below was copied from vendor pricing and help pages. Claude, Cursor, GitHub Copilot, Kiro, Bolt, Lovable, Devin and Augment Code pages were checked on 2026-10-30, the Claude Ultra help article on 2026-10-31, and OpenAI pages on 2026-11-01. The Copilot billing page and the Cursor pricing pages were re-read on 2026-11-02 and show the same figures. Plans change often, so readers should confirm on the vendor's site before buying.

The same $100 buys different kinds of answer

The clearest way to see the split is to line up what each vendor says about a $100 monthly plan.

Plan at $100 a month	What the vendor states	Countable monthly unit?
Claude Max	5x Pro usage every five hours and every week	No, a multiple of an unquantified base
ChatGPT Pro	No five-hour limit; weekly limits may still apply	No
Cursor Super	15x the Plus pool	No, a multiple of an unquantified base
Copilot Max	20,000 credits (10,000 base plus 10,000 flex)	Yes
Kiro Pro Max	5,000 credits	Yes
Lovable Pro	400 credits	Yes
Bolt	55M tokens (Help Center example)	Yes
Augment Business	$100 of usage	Yes

Nothing in the first three rows can be compared with the last five, or with each other. A buyer cannot say whether 5x Pro on Claude is more than 15x Plus on Cursor, because neither Anthropic nor Cursor says how big its base is. The $200 tier repeats the pattern: Claude Ultra at 10x Pro weekly, Cursor Ultra at 50x Plus, ChatGPT Pro at $200, Devin Max, Kiro Power at 10,000 credits and Lovable Pro at 800 credits.

Of the tools tracked, only Copilot, Kiro, Bolt, Lovable and Augment publish a countable monthly unit. Claude and Cursor publish only multiples, Devin publishes nothing countable, and OpenAI publishes per-model message ranges for Plus and Business.

Multiples of a hidden base

Claude's design is the most explicit about not giving numbers. Usage resets on a rolling five-hour session window, and paid plans add weekly limits that reset at a fixed time assigned to the account. Web, desktop, mobile and Claude Code draw from one pool. Anthropic publishes no fixed message count. It says usage depends on conversation length and complexity, attached files, the model, effort level and features used. Pro costs $20 and gets more usage than Free every five hours, but Anthropic no longer states a multiple of Free for Pro. The base of the whole ladder is therefore described only as "more than Free."

Above that base, the ladder is clean arithmetic. Max at $100 gives 5x Pro every five hours and every week, plus a separate weekly limit for Fable. Ultra at $200 drops the five-hour limit for verified accounts and gives 10x Pro weekly. Team standard seats at $25 give 1.25x the Pro per-session allowance, and premium seats at $125 give 6.25x. Against Pro's $20, those prices are 1.25 times and 6.25 times as large. The multiples therefore track price one for one, which suggests that Claude's tiers mostly sell more of the same thing in proportion. The open question is how much the thing is, and Anthropic does not say.

Cursor works the same way with a weekly pool. Every paid plan includes a pool for Cursor's own models (Grok 4.7, Grok 4.6, Grok 4.5 and Composer 2.5), and different models draw from it at different rates. Cursor publishes no request or credit counts. The tiers are Plus at $8 (the base), Premium at $30 (4x), Super at $100 (15x) and Ultra at $200 (50x). Here the multiples do not track price. Premium costs 3.75 times the Plus price for 4 times the pool. Ultra costs 25 times the Plus price for 50 times the pool. Per dollar, Ultra's pool is twice the size of Plus's, but a buyer still cannot say what the pool holds. A pricing ladder that rewards the biggest spender is easy to read, but the reward is measured against a base that is undisclosed.

Devin (Windsurf) is the limiting case. Each paid plan, Pro at $20 and Max at $200, gets an allowance that refreshes daily and weekly. Cognition publishes no credit, request or message counts, and extra usage is bought at API pricing. There is no unit to count, and none to compare.

Ranges and a coming switch at OpenAI

OpenAI is more specific than Anthropic or Cursor, and the specifics show how much a "number" can still leave open. Plus ($20) and Business ($25 per user per month, billed monthly, 2+ users) get Codex local-message estimates per five hours, given as a range per model:

Model	Local messages per five hours
GPT-6 Astra	5 to 45
GPT-6 Sol	15 to 150
GPT-6.1 Sol	15 to 160
GPT-6.1 Terra	35 to 285
GPT-6 Luna	350 to 3,000

Each range spans roughly eight to eleven times from bottom to top. OpenAI calls them "not fixed message limits." The count depends on the model, task size and complexity, and whether work runs locally or in the cloud, and cloud tasks may use more of the allowance than local messages. Weekly limits may also apply. A buyer planning a month of work from these figures is planning from a spread, not a quantity.

Other multipliers sit on top. Codex Fast mode uses included usage at 2.5x (2x on purchased credits), and Ultrafast at 8x (6x on credits). Image generation uses limits about 3 to 5 times faster. So the same plan delivers a different number of tasks depending on a mode setting. For Pro plans ($100, $200 and $500 a month), OpenAI says there is currently no five-hour limit, though weekly limits may still apply. That is a statement about a limit that is absent, not a quantity that is present.

The larger change is scheduled. OpenAI says that starting in December the usage allowance on Plus, Pro and Business will be shared across ChatGPT and Codex and measured in tokens, with Instant chat not drawing from it. It has not published per-plan token amounts. A move to tokens could make the allowance countable, but only if the amounts are published. This suggests the December figures are the thing to watch, and until they appear the token switch gives buyers nothing to count. Readers should confirm the amounts on OpenAI's site.

OpenAI's credit pricing already hints at what token metering looks like. After reaching limits, Plus and Pro users can buy credits billed per 1M tokens per model. For GPT-6.1 Sol the rate is 50 credits per 1M input tokens, 2.5 per 1M cached input tokens and 250 per 1M output tokens. Output costs five times as much as fresh input, and cached input one-twentieth. A call with 1M fresh input and 0.1M output would cost 50 plus 25, or 75 credits. The mix of work, not the number of messages, sets the bill.

Countable units still need a unit price

Five tools publish a monthly unit, and each one rewards a division that the vendor's page does not do for the buyer.

Kiro gives 50 credits per dollar on every paid tier: $20 for 1,000, $40 for 2,000, $100 for 5,000 and $200 for 10,000. That is $0.02 per plan credit at every tier, so a bigger plan buys no discount. Add-on credits cost $0.04 each, twice the plan rate. Plan credits do not roll over, while add-on credits roll over until they expire 12 months after purchase. Credits are metered to two decimal places with a 0.01 minimum. Simple prompts can cost less than 1 credit, complex ones such as spec tasks cost more, and models consume credits at different multipliers relative to Auto (1.0x). The count is exact, but the cost of a given task is not known in advance.

Copilot gives the most precise definition, since 1 AI credit equals $0.01. Pro at $10 has 1,000 base plus 500 flex credits (1,500 total). Pro+ at $39 has 3,900 base plus 3,100 flex (7,000 total). Max at $100 has 10,000 base plus 10,000 flex (20,000 total). Base credits match the subscription price, so Max's base is worth $100. At a cent per credit, the totals work out to $15, $70 and $200 of credit. That arithmetic is StackVersus's. The catch is that GitHub says the flex allotment may change over time. At Pro+, 3,100 of the 7,000 credits are flex, so the headline total is the less certain figure. Code completions and next edit suggestions do not use credits and are unlimited on paid plans. Included credits reset at 00:00:00 UTC on the first day of each calendar month. Business ($19 per user) adds 1,900 credits per user to a shared pool, and Enterprise ($39) adds 3,900. Paid plans get a 10% discount on model costs with auto model selection.

Lovable is linear on Pro: $25 for 100 credits, $100 for 400 and $200 for 800, all $0.25 per credit. Top-ups cost $0.30 per credit on Pro, and Business starts at $50 for 100 credits ($0.50 per credit). One balance covers building, chatting, hosting the built-in backend, AI features in deployed apps and connectors. A buyer can count credits, but what a credit buys depends on what the project does.

Bolt counts tokens, and the price per million falls with size in the Help Center examples. Pro starts at $25 for 10M tokens ($2.50 per million). The examples of 26M at $50 and 55M at $100 work out to about $1.92 and $1.82 per million. The unit is exact, but Bolt says most usage comes from syncing project files, so larger projects use more tokens per message. The same plan therefore yields fewer messages as a project grows. Unused paid tokens roll over and stay valid for two months.

Augment is the simplest on paper: Standard at $20 includes $20 of usage, and Business at $100 includes $100. But LLM usage is billed at the provider's API list price plus a flat 40% service fee. If the fee counts against the pool, $20 would cover about $14.29 of provider list-price usage. That is inference, and the vendor's billing page should settle it.

Overage is where the real price shows

The included allowance is the headline, but the overage rule shows what the vendor thinks a unit is worth. These rules vary more than the plan sizes do.

Claude lets paid users turn on usage credits billed at standard API rates when a limit is reached. Claude Enterprise includes no allowance at all: all tokens are billed at standard API rates, with a 20-seat minimum. Max and Ultra include $100 and $200 a month in API credits, but those work only on the Claude Platform, not in Claude Code or the Claude apps. Someone who buys Max for Claude Code gets no use from that credit there.

Cursor takes a different route to the same place. On Premium and above, third-party models such as Claude, GPT and Gemini sit outside the pool and are billed at API list price from the first request, out of prepaid credit. Free and Plus cannot use them. Teams and Enterprise pay an extra Cursor Token Rate of $0.25 per million tokens on eligible third-party requests. So the Cursor multiples apply only to Cursor's own models, and the larger tiers do not stretch the budget for the models many buyers name first.

Copilot charges $0.01 per credit beyond the pool, and paid extra usage is enabled by default, though admins can disable it. For a team that has not checked that setting, spend can run past the included credits. Kiro enterprise overage at $0.04 per credit is disabled by default, the opposite default. Free Kiro users cannot buy add-ons at all.

This suggests a practical reading. A plan with a countable unit and a safe default lets a buyer cap the worst case. A plan with a multiple of an unknown base and an open-ended overage at API rates makes the worst case hard to bound.

What to do

Pick the metering unit before the plan, and treat a plan with no countable monthly unit (Claude, Cursor's own pool, Devin, and OpenAI at least until it publishes token amounts) as a trial, not a budget line. For countable plans, divide price by units first: Kiro's $0.02 versus $0.04 add-on gap, Lovable's $0.25 versus $0.30 top-up, and Copilot's base versus flex split show where the headline overstates the guaranteed amount. Check the overage default before enabling a team: Copilot's paid extra usage is on unless an admin turns it off, and Kiro's enterprise overage is off. Finally, confirm every figure on the vendor's page on the day of purchase, because these pages change, OpenAI's token amounts are still unpublished, and GitHub says its flex credits may change.

Sources

Originally published on StackVersus, where prices and plan limits are checked against vendor pages and dated.

Why usage-based pricing is gaining ground on per-seat plans in automation tools

StackVersus — Mon, 02 Nov 2026 02:33:54 +0000

Automation tools are moving away from the idea that a person should pay for a seat. Zapier bills per task, Make bills per credit (called operations until August 2026), and n8n bills per workflow execution. Each meter counts something different, so the same automation can produce very different bills. The trend suggests that cost now follows how much automated work runs, not how many people log in. That is a better fit for teams that run many workflows with few users, and a harder one for teams that want predictable budgets.

The same workflow, three different meters

Consider a ten-step workflow that runs 1,000 times a month. On Zapier, that workflow is roughly 9,000 tasks. On Make, it is about 10,000 credits. On n8n, it is 1,000 executions, because n8n counts each run of the workflow rather than each step.

Tool	Billing unit	Approximate usage for a ten-step workflow run 1,000 times a month
Zapier	Task	About 9,000 tasks
Make	Credit	About 10,000 credits
n8n	Workflow execution	About 1,000 executions

These numbers are not a direct price comparison. Each platform includes a different allowance in each plan, and the price per unit varies by tier. The point is that the unit of measurement changes the apparent volume by a wide margin. A buyer who compares only plan names or monthly headline prices may miss how fast the units are consumed.

On n8n, the Community Edition is free to self-host. The n8n Cloud plan starts at 20 euros per month for 2,500 executions. Make Core is listed at $9 per month on annual billing. Readers should confirm current allowances, limits, and overage rules on each vendor's site, since those details change and are not covered here.

Why usage pricing fits automation better than seats

Seat pricing assumes that value scales with the number of people using a tool. Automation often works differently. A single operator can build workflows that run thousands of times a month without anyone touching the tool. Under a seat model, that operator's team might pay little while the system does a large amount of work. Under a usage model, the bill rises with the work.

This suggests that usage-based pricing aligns cost with the value a team gets from automation. It also means the cost is tied to decisions about workflow design. A workflow with many small steps may be expensive on a per-task or per-credit meter, while the same logic packed into fewer executions may cost less on a per-execution meter. Those trade-offs are inference based on how these billing units work, not a measured result from any vendor.

The model also rewards teams that can self-host. Because n8n Community Edition is free to self-host, a team with the technical capacity can remove the usage meter from its cost structure entirely. That option is likely to matter most for high-volume workflows, where any metered platform will charge the most.

Where the model has limits

Usage pricing makes budgets harder to forecast. A workflow that runs 1,000 times in one month may run 3,000 times the next after a new sales campaign or a data sync change. Teams that once paid a fixed amount per user may find their invoices swing with business activity. Finance teams often prefer predictable spend, so this is a real trade-off.

Seat pricing still has advantages for some organizations. It is easier to explain to a manager, easier to budget, and simpler to compare across vendors. A team with many light users and few heavy workflows may find seats cheaper or at least easier to control. The shift away from seats is therefore not universal. It is most visible in tools where the work happens in the background, not in the hands of named users.

What to do

Start by estimating how many runs each workflow makes per month, and multiply by the number of steps to see how each platform's meter would count them. Compare the same workflow on each vendor's current pricing page rather than relying on headline plan prices. If your workflows run at high volume, test whether self-hosting n8n is realistic for your team's skills and infrastructure. Set a monthly usage alert on any metered plan so that growth in automation does not turn into an unexpected bill.

Sources

n8n pricing

Originally published on StackVersus, where prices and plan limits are checked against vendor pages and dated.

What a 10-person team really pays for its SaaS stack in 2026

StackVersus — Sun, 01 Nov 2026 22:10:57 +0000

Every founder has a rough number in their head for what the software bill should be. Almost nobody has written it down. So we did, for the most common shape of early team: ten people, one product, a marketing function that is mostly one person and a newsletter.

The stack is deliberately boring. A workspace for documents, a tool for tasks, an automation layer, and an email platform. No CRM yet, no data warehouse, nothing a ten-person team should be buying before it has revenue to justify it.

The stack and what it costs at list price

Tool	Plan	Billing unit	Monthly at 10 people
Notion	Plus	per user	$100
ClickUp	Unlimited	per user	$70
Zapier	Professional	per account	from $19.99
Kit (ConvertKit)	Creator	per account, by list size	from about $33

Prices are the vendors' published annual-billing rates at the time of writing; confirm on each pricing page before you buy. Monthly billing typically adds 20 to 50 percent, depending on the vendor.

The total sits around $220 a month. That surprises people in both directions. Founders who have only ever seen enterprise quotes expect more. Founders who started on free tiers and have not looked since expect less, because the free tiers tend to run out as a team grows.

Where the money actually goes

Two of the four line items are per seat, and those two are 80 percent of the bill.

Notion and ClickUp together account for the bulk of the spend, and both scale linearly with headcount. Zapier and Kit scale with usage instead: tasks run and subscribers held. For a ten-person team usage-based pricing is almost always cheaper than per-seat, because most of those ten people never touch the automation or email tool directly.

The practical consequence is that hiring is the main driver of the software bill, not feature creep. Add five people and the per-seat tools add roughly $85 a month before anyone has asked for a new tool.

The duplicate-seat problem

The most common waste we see in small-team stacks is not an expensive tool. It is paying for the same person in two tools that overlap. Notion and ClickUp are the textbook case: both do docs, both do tasks, and most teams end up with everyone licensed in both while using each for half of what it can do.

There are two honest ways out:

Pick one. Teams that live in documents and only need lightweight task tracking can run on Notion alone. Teams that live in tasks, sprints and time tracking can run on ClickUp alone and tolerate its weaker docs. Either move cuts the per-seat line by roughly 40 percent.
Split the seats. Give the whole company the document tool and only the people who actually manage work the task tool. It is rare that all ten people need a ClickUp seat.

We walk through the trade-offs in detail in our ClickUp vs Notion comparison.

What changes at 25 people

The same stack at 25 people costs roughly 2.2 times as much, and that is before anything is added. Around this size the pattern shifts:

Per-seat tools start to justify their Business tiers, which cost more per user but add admin controls, SSO and audit logs that someone will eventually require.
Usage-based tools hit their plan ceilings. Zapier task limits and Kit subscriber bands are where the jumps happen, and they are lumpy: a single busy month can push you over.
A CRM appears, and it is nearly always per seat.

If you are budgeting for growth, model the per-seat tools against your hiring plan rather than against today's headcount. The sticker prices are not the story; the slope is.

What we would do

For a ten-person team starting today: one workspace tool, chosen by whether the team is document-first or task-first; one automation account on the cheapest tier that covers your task volume; and the free tier of the email platform until the list is big enough that it is paying for itself. That lands well under $150 a month and leaves room for the CRM you will need at 20.

Sources

Originally published on StackVersus, where prices and plan limits are checked against vendor pages and dated.

Per-execution pricing is quietly winning the automation market

StackVersus — Sun, 01 Nov 2026 12:10:09 +0000

For a decade the automation market competed on integrations: who had the most apps, who connected to the obscure tool your team happened to use. That race is largely over. Everyone has thousands of connectors, and the generic HTTP node covers the rest. The competition has moved to something less visible and more consequential: what, exactly, you are being charged for.

Three products, three meters

Zapier's unit is the task: every action step that runs counts as one, so a Zap with a trigger and three actions consumes three tasks per run. Make's unit is the credit (called an operation until August 2026), which is similar but counts every module run including the trigger; routers and error handlers are free. n8n's unit is the execution: one workflow run counts as one, however many nodes it touches.

Put the same workflow through all three and the meters disagree wildly. A ten-step workflow run 1,000 times a month is roughly 9,000 Zapier tasks, about 10,000 Make credits, and 1,000 n8n executions.

The price on the pricing page tells you almost nothing until you know what one unit of it buys.

Why the meter is drifting toward executions

Workflows are getting longer. The simple two-step Zap, new form response to new spreadsheet row, is a solved problem and nobody pays much for it. What teams are building now is multi-branch, multi-step logic: enrich a lead, score it, route it, write to the CRM, notify a channel, and increasingly call a language model somewhere in the middle.

Per-task and per-credit pricing penalise exactly that growth. Every added step is a line on the bill. Per-execution pricing is indifferent to it, which is why n8n's model reads as generous the moment a workflow passes five or six nodes, and why Make and Zapier have both been adding bundles and caps that soften their own meters.

Who this favours

Per-execution pricing favours technical teams building complex, high-volume automations, and those are the teams most likely to tolerate self-hosting. n8n's free Community Edition makes the meter zero for anyone willing to run a server.

Per-task pricing still favours the long tail: marketers and operators running dozens of small, simple automations, where the ease of Zapier's editor and the depth of its integrations is worth more than the unit cost.

Make sits in between, and its pricing shows it: the cheapest entry tier of the three, with a meter that becomes expensive faster than it looks.

The practical takeaway

Before choosing an automation platform, count the steps in your three most important workflows and multiply by the runs you expect per month. Then price that number, not the plan name, on each vendor's page. We did this for the two most common alternatives to Zapier in our Make vs n8n comparison and the Zapier vs Make comparison; the cheaper tool flips depending on the shape of the workflow.

Sources

Originally published on StackVersus, where prices and plan limits are checked against vendor pages and dated.

What a minute of an AI phone call costs across Vapi, Retell and ElevenLabs

StackVersus — Sun, 01 Nov 2026 09:45:34 +0000

A headline per-minute price tells you little about what an AI phone call costs. The figures in the StackVersus voice directory, checked on 2026-10-30, show three different billing models. Vapi and Retell charge a platform fee and pass through the model components. ElevenLabs Agents bundles voice and transcription into a per-minute price and bills the language model on top. Our reading is that the lowest-looking fee is rarely the lowest total cost. Volume, call length and the voice you need will decide the answer.

Vapi's low fee is one line of several

Vapi charges a platform fee of $0.05 per minute, prorated to the second. Its pricing copy says transcriber, model, voice and telephony costs are "charged at-cost" on top of that fee. Telephony, SIP, WebSockets and Daily WebRTC are listed as free.

Vapi's own calculator defaults show how the stack adds up. Deepgram speech-to-text runs $0.0095 to $0.0099 per minute, OpenAI's LLM runs $0.0077 to $0.0452 per minute, and ElevenLabs text-to-speech runs $0.0146 to $0.0238 per minute. Its 1,000-minute example totals $82 to $129 per month.

This suggests the $0.05 headline is a floor, not a quote. The final figure depends on the model, voice and transcriber you select, and each one moves the bill.

Vapi's plan structure also matters for volume. The free No Success Package allows 4 concurrent calls. Core, at $29 per month, allows 10. The Pro plan starts at $999 per month for 30 concurrent calls. Teams that need concurrency will likely cross into a fixed monthly commitment well before they reach a large call volume.

Retell's range is wide by design

Retell bills per minute, timed to the nearest second and summed across the billing cycle, with no per-call rounding up. Its Voice Infra platform fee is $0.055 per minute. The advertised all-in range is $0.07 to $0.31 per minute.

That gap is the most useful number in this comparison. The bottom of the range likely reflects inexpensive voices and models. The top likely reflects premium voices and heavier prompts. Voice choice drives most of the spread. The directory lists voice options from $0.015 per minute up to $0.10 per minute, so a reader who needs a specific premium voice should expect a higher bill.

Retell's billing also has gotchas that can raise cost. Calls under 10 seconds that use a dynamic opening message are billed a 10-second minimum. Prompts over 4,000 tokens scale billed duration, using the prompt's LLM token count divided by 4,000. Silence and hold time are billed because speech-to-text keeps listening. Short-call and long-prompt workloads should be modeled before a team commits.

ElevenLabs trades itemization for predictability

ElevenLabs Agents includes call minutes in each plan and charges $0.080 per minute for additional calls on all self-serve plans. Burst pricing above the concurrency limit is $0.160 per minute. Speech-to-text is listed under included features, and telephony passes through at cost.

The plan math is consistent. Creator at $22 for 275 minutes works out to $0.08 per included minute. Pro at $99 for 1,238 minutes and Business at $990 for 12,375 minutes both come to $0.08 per minute. The paid tiers price minutes at the same rate that overage is billed, so a team that knows its volume can forecast its voice cost precisely.

The LLM is the exception. ElevenLabs passes through third-party LLM costs "at the provider's published rate, with no markup," but select Gemini and Claude models carry a 10 percent uplift on Vertex AI regional rates. For example, gpt-4o-mini lists at $0.15 per million input tokens and $0.60 per million output tokens. Teams that want a particular model should confirm its current rate on the vendor's site.

Vendor	Billing model	Voice and transcription	LLM
Vapi	$0.05/min platform fee plus at-cost components	Itemized	Itemized
Retell	Usage-based per minute, advertised $0.07 to $0.31 all-in	Itemized	Itemized
ElevenLabs Agents	Included minutes, $0.080/min overage	Bundled	Passed through at provider rate

What to do

Start with your expected monthly call minutes, average call length and concurrency needs. Model the LLM and voice you plan to use on each vendor's calculator. Check the minimum billable duration and prompt size, because both can change the bill for short or prompt-heavy calls. Confirm current rates on each vendor's pricing page before you decide, since figures can change.

Sources

StackVersus voice directory (vendor pages checked 2026-10-30)

Originally published on StackVersus, where prices and plan limits are checked against vendor pages and dated.

ChatGPT and Codex will share one usage allowance from December

StackVersus — Sun, 01 Nov 2026 09:44:08 +0000

OpenAI has updated its Help Center article on ChatGPT and Codex usage limits to say that, starting in December, the usage allowance on Plus, Pro and Business plans will be shared across ChatGPT and Codex. The change comes as OpenAI brings the agentic capabilities of Work into the main ChatGPT experience.

Usage for both products will be measured in tokens. How much of the allowance a task uses depends on the model chosen and the task itself, and more advanced models and complex tasks generally use more. Instant chat will not draw from the allowance. Combined remaining usage and reset times will appear in Settings > Usage.

OpenAI says it is preparing carefully to prevent disruption and expects most users won't need to wait for usage to reset more often than they do now. At the limit, users can wait for a reset, upgrade their plan, or buy credits to keep using eligible features.

The article does not give an exact December start date, token amounts per plan, or new five-hour or weekly figures. A separate OpenAI page on using Codex with a ChatGPT plan, updated about a week earlier, still says Pro plans currently have no five-hour limit and lists Plus local-message ranges per five hours. Those pages do not yet fully align with the shared model.

Why it matters

Developers and teams that split work between chat and Codex will draw from one pool, so a heavy coding session could leave less room for chat, and the reverse. Model choice also becomes a bigger cost lever, since advanced models consume more of the allowance per task.

What to do

Once the change takes effect, check Settings > Usage to see your combined remaining allowance and reset times. Confirm the December start date, per-plan token amounts and current five-hour limits on OpenAI's site before changing plans or budgets. If you rely on a heavier model, test your typical tasks now to estimate how quickly they draw down the shared pool.

Sources

OpenAI Help Center

Originally published on StackVersus, where prices and plan limits are checked against vendor pages and dated.