Copilot Credit Estimator¶

New here? Take the quick tour — then everything below is yours to explore.

📺 Watch the full walkthrough (3½ min)

All four ways to estimate — Quick, Quick + Import, Detailed, and Solution package — plus the full journey from estimate, to ROI, to a finished proposal.

Estimate monthly Copilot Credits for Copilot Studio agents or Copilot Cowork. Runs in your browser — nothing is uploaded. Numbers are directional and the tool is still evolving; for Microsoft's own figures, see the official Copilot Credit Estimator.

Where do you want to start?

Describe what you want the agent to do

Try an example:

We read your description to pre-fill a short guided assessment, then estimate the Studio build effort and a credit/cost profile — a directional starting point, not a real LLM analysis. Answer the questions, then open it in the Detailed estimator. Once your estimate is ready, you can also download a ready-to-import Copilot Studio starter agent (.zip) generated from your description.

Paste a customer conversation, email, notes, or a transcript

The tool reads your text, finds the use case(s), sizes each as a Copilot Studio agent or an M365 Copilot (Cowork) adoption, and rolls them into one milestone-ready recurring number. Everything below is editable.

Try:

🧠 Structure with Copilot (higher fidelity)

Paste your messy text into Microsoft 365 Copilot with this prompt to get clean use-case rows, then paste them back above.

Directional starting point, not a real LLM analysis — verify before quoting. Steady-state assumption: month-1 run-rate ≈ ongoing monthly consumption, which is what you'd turn into a recurring MSX milestone.

Upload a built agent or flow package

Drop a Dataverse solution export (.zip) — a Copilot Studio agent, a Power Automate cloud flow, or both — or a curated agent build-spec bundle. We inventory topics, knowledge, actions, flows (with AI Builder prompts, loops and connectors), and multi-agent orchestration, then size it and estimate credits. The file is parsed entirely in your browser — nothing is uploaded to any server.

Drop your solution / package .zip here

or click to choose a file

What can I upload?

A. Dataverse solution export (most accurate):
1. Go to make.powerapps.com → Solutions.
2. Create a solution (or open an existing one) and add your Copilot Studio agent and/or Power Automate flows — plus their connection references.
3. Choose Export solution → Unmanaged or Managed → download the .zip.
4. Drop that .zip above. We read the agent/topic YAML and workflow JSON to inventory components.

B. Power Automate flow only: export just the flow's solution — we parse its trigger, actions, AI Builder prompts, loops and connectors, and treat it as an autonomous (per-run) workload.

C. Agent build-spec bundle: a folder of build docs (.md) + knowledge files (.docx/.pdf) zipped together — we infer knowledge sources, actions, orchestration and guardrails from the spec.

1 · Download the template

Grab the workbook, fill in one row per scenario on the Scenarios sheet (the Examples sheet is prefilled to copy from), then bring it back here. Every scenario gets a T-shirt size, a credit/cost estimate and a build read-out, plus a portfolio roll-up. Everything runs in your browser — nothing is uploaded.

Tip — let Copilot fill the sheet for you. You don't have to fill the Scenarios sheet by hand. Ask Microsoft 365 Copilot to populate it from a plain-English list of your agents — one row each — then re-upload. The example prompt is copy-paste-ready. Pick Copilot Chat (default, concise) or Cowork (a step-by-step analyst brief) below, hit Copy prompt, then just replace the My agents list at the bottom with your own and send it to Copilot; it uses the prefilled Examples sheet as the pattern, infers each column, and leaves unknowns blank.

You're helping me fill in the 'Scenarios' sheet of this Copilot Credit Estimator workbook, to paste back into the sheet. Use the prefilled 'Examples' sheet as the pattern and add one row per agent from my list below. Infer each column from my descriptions and leave a cell blank if it isn't implied — don't invent enum or number values. For the Harness column, use 'GitHub Copilot' for reasoning-heavy, multistep/agentic agents and 'Standard' for rule-based Q&A / topic agents.
My agents (one per line — what it does, who uses it, how often, channel, knowledge, actions, and standard vs GitHub Copilot harness):
1)
2)

Copilot's inferences are a starting point — sanity-check the enum/number columns before importing.

2 · Import your filled-in workbook

Drop your filled-in .xlsx or .csv here

or click to choose a file

What do the columns mean?

Describe your agents — one per line

Paste a plain-English description of each agent on its own line and get a ready-to-import Copilot Studio starter (.zip) for every one, bundled together with a portfolio roll-up. This mirrors Quick + Import, but the output is generated agents, not just sizing. Everything runs in your browser — nothing is uploaded. These are directional starters to extend, not production-ready agents.

Want more control? Use a header row.

Without a header, each line is treated as one agent description. To set options per agent, make the first line a header naming any of: name, description, experience (new/classic), archetype (interactive/autonomous), knowledge, workIQ (yes/no), skills (;-separated), systems (;-separated). Separate columns with a comma or tab; wrap any value containing a comma in "quotes". description is the only required column. New experience is the recommended default.

Try an example set:

How to use this estimator

Set your org scope — enter the number of users you're modelling and the proportion with an M365 Copilot license.
Choose deployment type — Microsoft 365 (Teams · Copilot Chat · SharePoint) means licensed users accrue zero credits; Standalone / other channel charges all users regardless.
Set interaction frequency — estimate how many times a typical user interacts with the agent per month.
Build your normal path — for each row, set Uses / interaction to how many times that feature fires in a single interaction. Rows default to 0 — only count features your agent actually uses.
Add an escalation path (optional) — set an escalation rate and add extra steps that only fire when an interaction escalates (e.g. a query that can't be self-served triggers an additional lookup or handoff). The rate controls what percentage of interactions incur these extra costs.
Check the results — Credits / month (org) and Credits / user / month are the numbers to share with finance or IT for budget planning.

Agent type

Interactive agents are driven by people — a user sends a message or makes a call. Credits scale with users × interactions / month, and M365 Copilot–licensed users can accrue zero credits on Microsoft 365 surfaces (Teams · Copilot Chat · SharePoint).

Quick presets

Deployment type

On Microsoft 365 surfaces (Teams · Copilot Chat · SharePoint), M365 Copilot licensed users incur zero credits. Only unlicensed users generate credit consumption. Use the % with M365 Copilot license slider to set the licensed proportion.

Harness (Copilot Studio engine)

Standard & Copilot chat are covered by an M365 Copilot license in M365 channels. The GitHub Copilot harness is never covered — every interaction bills credits, so net billable = gross.

Organization

Total users in scope

Employees, contractors, or team members you're modelling

% with M365 Copilot license

%

Microsoft 365 surfaces (Teams · Copilot Chat · SharePoint): licensed users accrue zero credits — only unlicensed users are billed. Pilots typically 10–20 %; full rollouts 60–100 %

Avg interactions / user / month

How many times does a typical active user interact with this agent each month

Events / month

How many trigger events the agent processes each month — inbound emails, uploaded documents, queue items, records, etc. Every event is billed (no per-user licensing discount).

Escalation rate

%

% of interactions that require additional handling beyond the normal path

Edit rows or add your own process steps

📞 Voice rows are per minute. In the Uses / interaction column, enter the average voice minutes per conversation — it's multiplied by your interactions × users to get the monthly total (credits = rate × minutes). The per-minute voice rate already includes the classic / generative answers and agent actions that occur during the call, so don't also fill in those rows for a voice agent. Tenant-graph grounding, content processing, AI tools, and agent flows are billed separately on top.

Agent feature / interaction type	Uses / interaction	Credits / use	Credits / interaction
Escalation path — 0% of interactions trigger these additional steps
Effective credits / interaction			—

Estimated monthly consumption

—

Unlicensed users (billed)

—

Total interactions / month

—

Credits / month (org)

—

Credits / user / month

Budget check (optional)

Monthly credit budget

Enter a monthly credit budget above to see headroom or overage against your estimate.

How do you want to estimate?

Cowork is estimated top-down: model a population — licensed users × how many are active × how many credits each active user burns a month. These are directional planning numbers; tune every input. Everything runs in your browser.

Model your population

Licensed users People you'd turn Cowork on for.

Active usage rate %

Share of licensed users active in a month.

Avg credits / active user / month

The primary driver. Tap a persona to use Microsoft's published band, or enter your own.

Model a conservative–liberal range Optional — set low/high ends for active usage and credits/user to bracket the estimate.

Active usage % — conservative

Active usage % — liberal

Credits/user — conservative

Credits/user — liberal

Global assumptions (price, discount, license floor, budget)

Price per credit ($) Pay-as-you-go list rate.

Azure discount %

Include M365 Copilot license floor Flat $ / licensed user / month, added to spend.

Monthly budget cap ($) 0 = no cap.

Credit & price mechanics follow public Microsoft Learn (PAYG $0.01/credit; $200 / 25,000-credit pack). Persona presets use the bands in Microsoft's official Copilot Credit Estimator (retrieved 2026-10-28); active-usage % is a neutral planning anchor.

Estimated monthly consumption

—

Active users

—

Credits / month

—

Cowork spend / month

—

Cost / active user / mo

Cohorts

Split the population into groups (by role, region, or business unit) and tune each. Avg credits/user/mo is the primary driver.

Intensity helper optional — estimate a credits/user number from a prompt mix

Light prompts / mo

Medium prompts / mo

Heavy prompts / mo

≈ credits / user / mo

—

Illustrative weights (125 / 500 / 2,500). Type this into a cohort.

Global assumptions (price, discount, license floor, budget)

Price per credit ($)

Azure discount %

Include M365 Copilot license floor

Monthly budget cap ($)

Credit & price mechanics follow public Microsoft Learn. Active-usage % and credits/user are neutral planning anchors, not official Microsoft figures.

Model a conservative–liberal range Optional — brackets every cohort's active usage and credits/user by ±buffer to show a roll-up range.

Range buffer ±%Applied to both drivers, every cohort.

Roll-up

—

Active users

—

Credits / month

—

Cowork spend / month

—

Cost / active user / mo

Adoption forecast

Monthly growth %Adoption ramp, month over month.

Forecast horizonHow far to project the ramp.

Start from your tenant's real numbers. In the Microsoft 365 admin center → Reports → Usage → Microsoft 365 Copilot, export the Consumption report (per-user monthly credits used & limit, license, sessions) — or the older Credits report (measured credits per user) or Copilot Chat usage report (active users & prompts). Drop the CSV below — or paste the four dashboard totals, or a screenshot. Everything is parsed in your browser; nothing is uploaded.

1 · Bring in your data

Drop a CSV export (Consumption, Credits, or Chat usage) or a dashboard screenshot here, or .

CSV gives the richest result — per-user rows become measured credits/user with power-user outlier and credit-cap flags. A Consumption export also auto-detects your licensed population.

…or paste the four dashboard numbers

Active users

Avg daily active users

Total prompts submitted

Avg prompts / user

2 · Licensed users in scope

Licensed usersAuto-filled from a Consumption export's license column. For Credits/Chat reports (active users only), enter the licensed population so we can compute active-usage %.

3 · What we found

Import a file or paste totals above to see a summary.

Not sure GitHub Copilot is the right engine?¶

For a could-go-either-way agent, the deciding factor is often cost structure, not features — GitHub Copilot bills per token (grows with payload) while Microsoft 365 / Copilot Studio bills per event (flat per turn). The Cost Structure Comparator shows which wins for your workload shape and where the crossover sits.

Building a customer-facing voice or chat agent? (Customer Conversation harness)

Copilot Studio's newer Customer Conversation harness — customer service over web chat or a phone number, with hand-off to a human — bills per conversation in Copilot Credits and is never covered by a Microsoft 365 Copilot license. Microsoft publishes these illustrative ranges per conversation (billing overview, diagram, retrieved 2026-10-28):

Scenario	Digital chat	GenAI voice	Premium (S2S) voice
Light — simple FAQ or confirmation (~2 min voice)	5–15	20–30	34–44
Medium — multi-turn, one or two tools (~5 min voice)	15–25	50–75	85–110
Heavy — reasons across facts and tools (~10 min voice)	25–50	100–150	170–220

Multiply by conversations per month for a first read, or model it in Microsoft's official Copilot Credit Estimator (Contact Center Intelligence).

What to do with this number

Credit budget planning — share the monthly credit estimate with your IT/finance team alongside the licensed user count to validate your M365 Copilot SKU allocation.
Adoption benchmarking — as real usage data comes in from the admin center, compare actuals to this estimate to see whether adoption is ahead or behind plan.
Scenario planning — run the estimator at 3 adoption-rate levels (conservative / target / optimistic) to bracket your credit spend.

How it works & billing details¶

Reference material — the credit billing rules and a full how-to for every mode. The estimator above works without reading any of this.

How Copilot Credits are billed — rates & licensing

Rates are sourced from the Microsoft Copilot Studio Billing rates and management docs. Each agent turn may combine multiple features (e.g. a generative answer with tenant graph grounding = 2 + 10 = 12 credits).

Key licensing rule: For employee-facing agents on the standard harness, users with an M365 Copilot license accrue zero credits when the agent runs under their own authenticated identity (for example in Microsoft 365 Copilot Chat, Teams, or SharePoint) — as of October 2026 Microsoft's rate table shows "No charge" for every standard-harness feature for licensed users, within fair use. Only unlicensed users generate credit consumption. When deployed to an external or anonymous channel (public website / web widget, customer-facing app, etc.), all users are charged credits. Use the Deployment type toggle in the Detailed mode to model the correct scenario. The GitHub Copilot and Customer Conversation harnesses are never covered. Pick the Harness in either mode and the estimator shows gross consumption vs. net billable side by side. (The estimator's "Copilot chat" harness option reflects older guidance and is being retired — Microsoft now lists three harnesses: GitHub Copilot, Customer Conversation, and standard.)

Zero-rating exceptions

A few official cases where a Microsoft 365 Copilot license does not zero-rate usage (per the billing-rate footnotes):

GitHub Copilot harness agents are never covered by a Microsoft 365 Copilot license — every interaction, plus building and testing the agent, bills Copilot Credits regardless of channel. Only the standard harness is zero-rated. Use the Harness selector to model it. Microsoft bills this harness per task by complexity and shows credit ranges only in a diagram on its billing overview — Light 100–300 · Medium 300–500 · Heavy >500, treat as illustrative — that bundle model tokens, tools, and the harness itself (there is no per-action rate card for this harness, so the estimator hides the per-action grid and prices a task at an editable credits-per-task anchor seeded from the tier). The anchors sit toward the high end of each band to lean slightly conservative, and Heavy is open-ended (editable upward, no cap). A one-time build & test cost is added on top.
Model choice is the largest single cost driver on the GitHub Copilot harness. The published tier bands are model-blind, but the LLM-token cost of a task swings roughly 10–20× between a lightweight model and a frontier/reasoning model. In Quick mode (open Edit all variables) or Detailed mode, pick a Model to switch the per-task estimate from the flat tier anchor to a per-turn token build-up: credits/task ≈ turns × ((overhead + payload) × in-rate + output × out-rate) ÷ 1,000, floored to Microsoft's published Light band (100), priced per model and net of a cache-hit % lever (re-sent context bills at ~10% of fresh input — the dominant way to control agentic burn). This is the same engine as the standalone comparator. Model rates are derived from GitHub Copilot's published per-1M-token pricing converted at 1 credit = $0.01, and remain directional — verify before quoting. Choose No specific model for the published-band estimate.
Computer-Using Agent (CUA) actions are not included in the Microsoft 365 Copilot license — they bill at the agent-action rate (5 credits) even for licensed users.
Agent flow actions are "no charge" for licensed users only when the flow uses the "When an agent calls the flow" trigger. Agent flows on any other trigger consume credits at the standard rate.
Generative answers are zero-rated on Microsoft 365 surfaces / in Agent Builder only when they run without tenant-graph grounding — tenant-graph grounding always meters (10 credits/message).

Benchmarked against Microsoft's official tools. This engine's rate card and per-turn math are calibrated to match the public Copilot Studio agent usage estimator and the Learn billing doc — all base rates (classic 1, generative 2, agent action 5, tenant-graph 10/msg, flow 0.13/action, AI 0.1/1.5/10, voice 10/35/75) align, as do the doc's worked examples (a tenant-graph-grounded turn totals ~12 once the generative answer is added). Two nuances it now follows: an autonomous trigger is billed as one agent action (5) — not a flat surcharge — with the actions it invokes billed separately; and when a reasoning-capable model is detected in a solution package, a premium 10 credits / 1K tokens meter is added on top of the feature rate. Reasoning surcharges are otherwise assumed off (standard models).

??? note "Copilot Cowork — usage-based billing" Copilot Cowork (generally available since June 16, 2026) requires a Microsoft 365 Copilot license and bills every task in Copilot Credits on usage — the license does not zero-rate Cowork. A task's cost comes from model use, context retrieval, tool calls, and runtime. Admins grant access with a spending policy in the Microsoft 365 admin center (Copilot → Cost Management), with per-user or per-group monthly limits that reset monthly; users can type /cost in Cowork to see what a task used (credit usage for Cowork tasks). Pay-as-you-go is $0.01 per credit, or commit with a pre-purchase plan (P3) for a discount. Microsoft also publishes its own Cowork cost estimator spreadsheet (light / medium / heavy tasks by persona).

   Unlike Studio, you don't inventory components for Cowork — you forecast a **population**: *licensed users × monthly active-usage % × avg credits per active user*. Ground it in your tenant's real numbers with the admin center's **[Copilot Credits / Consumption report](https://learn.microsoft.com/en-us/microsoft-365/admin/activity-reports/microsoft-365-copilot-credits)** (per-user measured credits, monthly limit &amp; license) or the **[Copilot Chat usage report](https://learn.microsoft.com/microsoft-365/admin/activity-reports/microsoft-copilot-usage)** (active users, prompts/user); the **Import from M365** mode reads any of these CSV exports. The per-user Consumption export additionally auto-detects your **licensed population**, separates **active vs. provisioned-idle** users, and flags anyone **pinned at their credit cap** (whose usage understates true demand, so the average is treated as a floor). The active-usage % and credits/user *defaults* in this estimator are neutral planning anchors — **not** official Microsoft figures — so adjust them to your data.

New here? How to use this estimator

First, pick what you're estimating — Copilot Studio agents or Copilot Cowork — using the switch, then choose how you want to estimate. The two products use different methods (Studio inventories what you built; Cowork forecasts a population), so each has its own modes. Every mode runs locally in your browser; nothing is uploaded.

Mode	Best when…	What you provide	What you get
Quick	You're early or unsure and just want a ballpark.	A plain-English description of the agent (or an example chip).	A T-shirt size, a Studio build outline, and a credit/cost range.
Quick + Import	You're sizing many agents — a whole portfolio — at once.	An Excel workbook with one row per scenario.	Per-scenario sizes and credits, plus a portfolio roll-up.
Detailed	You know the building blocks but haven't built yet.	Org scope, deployment type, and the features each interaction uses.	Credits per month and per user, ready for finance or IT.
Solution package	The agent is already built.	A Copilot Studio solution export (`.zip`).	A component inventory, a T-shirt size, and a credit estimate.

Estimating Copilot Cowork instead? Flip the switch to Copilot Cowork — it uses a population-based method (model licensed users × active-usage % × credits per active user), with its own modes:

Cowork mode	Best when…	What you provide	What you get
Quick	You want a fast org-wide ballpark.	Licensed users, an active-usage %, and avg credits/user.	Monthly credits, spend, annual, and a message-pack / pre-purchase plan.
Detailed	You want to model cohorts (roles, business units).	One row per cohort, tuned individually.	A roll-up plus a 6-month adoption forecast; open any Quick estimate here to refine.
Import from M365	You have real admin-center data.	The Copilot Credits or Chat usage CSV export (or the four dashboard totals).	Editable cohorts seeded from your measured credits/user, with power-user outliers flagged.

QuickQuick + ImportDetailedSolution package

Select the Quick card (the default).
Type a plain-English description — what it does, who uses it, how often, and where it runs — or click an example chip.
Click Build my estimate →.
Answer the short guided follow-ups.
Review the size, build outline, and credit/cost range.
Optionally open it in the Detailed estimator to refine.

Select the Quick + Import card.
Click ↓ Download Excel template (.xlsx).
Fill the Scenarios sheet — one row per agent or use-case (the Examples sheet is prefilled to copy from).
Drop the completed workbook back on the page.
Review each scenario's size and credits, plus the portfolio roll-up.

Select the Detailed card.
Follow the six in-panel steps: set your org scope, choose the deployment type, set the interaction frequency, fill the per-interaction feature rows, add an optional escalation path, then read the results.

Select the Solution package card.
In make.powerapps.com, add your Copilot Studio agent — plus any Power Automate flows and connection references — to a solution and Export it as an unmanaged .zip.
Drop the .zip on the page.
Review the component inventory, size, and credit estimate.
See the panel's "What can I upload?" note for the A / B / C upload options.

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