GitHub Copilot Fusion: Pricing and Limits (2026)
Oct 31, 202611 min read
As of 2026-10-31, the day its page was checked, GitHub Copilot Fusion counts as a new feature of GitHub Copilot, much as teams wiring up automations in tools like Activepieces treat each fresh addition as something to evaluate rather than assume.
I have no release date to give, so I won't invent one.
GitHub Copilot Fusion: what was released and when
What GitHub released
The name "Fusion" appears on GitHub's page only as a link to the docs. Its "Let Copilot choose" item describes matching each task with one or more models, and that item links to the GitHub Docs page for Copilot Fusion.
That description is the only definition used here. Anything beyond it, such as how the choice is made or what it costs, isn't established, so a team shouldn't plan around it.
The "Let Copilot choose" item reads as aimed at people who'd rather not pick a model for every task. The page offers nothing I can quote about workflows, APIs or triggers. If you automate, that gap is the first thing to hold against it.
Every claim here comes from GitHub's feature page and the docs page it links to, read on 2026-10-31. Vendor landing pages tend to lead with the pitch.
Activepieces is easier to check than to read: its connector detail is a public catalog of pieces, so you can see which integrations currently exist.
A headline tells you the pitch, not which trigger fires or which field maps, and a directory does.
GitHub's page gets the same reading: what it states counts, and the rest waits for the sections that test it against a workflow.
If you are running this arithmetic for your own team, see what the same workload costs on Activepieces.
Why Copilot Fusion matters to automation teams
It matters only if a workflow can reach it. A coding assistant that works in an editor but can't be called from a trigger or a step is a tool for one person, not for the process you automate.
That's the reading to apply to what GitHub's page states about Fusion.
A coding assistant that works in an editor but can't be called from a trigger or a step is a tool for one person, not for the process you automate.
Where it meets automated work
A coding assistant touches automation at a handful of points, and each one has its own failure mode:
- Repositories and pull requests, where its output lands for review
- CI runs, where its changes get tested
- Issue triage, where something has to read and label incoming reports
- Deploy scripts, where a bad edit costs the most
- The workflow step that would have to call it
The last item decides the rest. If nothing in a workflow can invoke the assistant, the other four are manual handoffs with a person copying results between them.
Read the pull request chart below as wider context on work moving through GitHub, not as a Fusion figure. It is only a sign that pull requests are a busy surface, and that any assistant writing to them adds to a queue someone already reviews.
Which of these points Fusion covers is a separate question, and the page has to answer it.
Ask whether a workflow can start it, pass it an issue or a branch, and receive a pull request back without a person in between.
Ask where it runs, what it can write to, and whether your CI checks gate its changes. Where the page is silent, treat the answer as unknown.
What is new in Copilot Fusion
Nothing measurable about Copilot Fusion is confirmed yet: no price, usage cap or plan list carries a figure we can quote, so the unknowns below stay unknown.
We have no stated capability with a number attached. Without one, a team can't tell whether Fusion does anything its existing Copilot setup doesn't. Judge it on stated behavior, not on the launch headline.
Read the middle column of the table as the whole list of usable facts, and the right column as what you must ask GitHub before building on it. The table shows what we can and can't take from GitHub's page.
| Item | What GitHub's page states | What the page does not say |
|---|---|---|
| Access route | No confirmed route | Whether it lives in the editor, on github.com or in a CLI |
| Eligible plans | No confirmed list | Which tiers, personal or organization, include it |
| Price | No confirmed figure | Whether it is bundled or billed separately |
| Usage limits | No confirmed figure | Any cap, quota or rate limit |
| API or webhook | No confirmed availability | Whether a workflow can trigger it or read its output |
Prices and plan limits checked against github.com and activepieces.com and docs.claude.com and claude.com and openai.com and gemini.google on October 31, 2026.
The last row decides the most. If a workflow can't call Fusion, it's a manual tool, however capable.
Every right-hand cell above is a gap. Until GitHub fills them, don't budget for Fusion or wire it into an automation, and don't assume it inherits terms from other Copilot features.
What Activepieces has already shipped for Copilot Fusion
Activepieces has shipped nothing dedicated to Copilot Fusion that we can point to, so the only route to Fusion today is the generic GitHub integration, which sits in the MIT-licensed core.
19 actions and 14 triggers are listed for the GitHub integration in the Activepieces catalog. Those cover GitHub in general, not Fusion by name, so read the count as breadth of GitHub coverage and nothing more.
That GitHub integration is one of the 746 integrations counted in the MIT-licensed packages/pieces/community directory of the open source repo, which means you can fork the connector to fix or extend it. Each one is a integration, and a integration action is defined once there.
The Integrations Framework and MCP Server documentation describe how that single definition runs as a step in a flow and is also exposed as a tool on Activepieces' per-project MCP server, so Claude, Cursor or an agent you built can call the GitHub actions without a second integration.
If GitHub documents an endpoint for Fusion, it reaches both routes once it is connected.
We haven't run Fusion ourselves, and what follows rests on GitHub's page and the 19 actions and 14 triggers Activepieces lists for GitHub.
Connecting it in a workflow today
Most of what you would automate is reachable, and one part stays a manual step.
Because the unscriptable surface can't be driven from a flow, build around the three that can be.
- Add the GitHub trigger to a new flow.
- Send the event to a webhook step.
- Add an HTTP request step pointed at the endpoint GitHub documents for that surface.
- Store the access token as a connection, never inline in the step.
- Test on one low-risk repository before widening scope.
If GitHub's documentation doesn't name an endpoint for your surface, stop at step 2. A flow that only receives events still tells you whether Fusion is worth wiring further.
Worth checking against a plan that does not meter every step: one credit covers a whole run on Activepieces.
Compare Copilot Fusion cost and speed to alternatives
As of 2026-10-31, Fusion can't be ranked on cost or speed. Neighbouring plans publish prices, and none of the options compared here publishes a speed figure a workflow could be timed against.
viz type=groupedbars title="What Copilot individual plans cost against credits included" unit="$ per month" source="GitHub - https://github.com/features/copilot/plans" cols="Monthly price,Monthly credits"0 and includes viz type=groupedbars title="What Copilot individual plans cost against credits included" unit="$ per month" source="GitHub - https://github.com/features/copilot/plans" cols="Monthly price,Monthly credits"00 and includes $200, so credits exceed price on both." Pro: 10, 15 Max: 100, 200
Copilot Fusion pricing per seat and per use
On GitHub's plans page, Copilot Pro is listed at $10 per month and Max at $100 per month. Those are ranges, so budget at the top figure until a checkout says otherwise.
Google's Gemini subscriptions page lists AI Plus at $4.99, AI Pro at $19.99 and AI Ultra at $99.99 per month, so the tier you choose determines your monthly cost.
A team already on AI Pro pays more than Copilot Pro's top figure and far less than Max's floor.
Anthropic's pricing page shows a $0 Claude Free plan with limited usage every 5 hours, a free baseline for testing before anyone pays.
The table sets Fusion beside both. Read the "not published" cells as the finding, because those are the numbers you can't budget or schedule around.
| Published price | Access route | Published speed figure | |
|---|---|---|---|
| Copilot Fusion | Not published | GitHub Copilot; workflow route unconfirmed | Not published |
| Other GitHub Copilot plans | Pro $10–$15, Max $100–$200 per month | GitHub subscription | Not published |
| Team's current assistant | $0 to $99.99 per month, depending on tier | Vendor subscription | Not published |
Without a Fusion price, any pilot's cost is an assumption you'd be writing yourself.
No speed comparison can honestly be made today. GitHub publishes no Fusion figure, and the other pages cited here publish none either. Any ranking would be invented.
Timestamp the moment your flow receives the event and the moment the result lands, then compare those intervals against your current assistant on the same task.
Next steps for adopting Copilot Fusion this week
Once you have your own intervals, the next question is what'll change under them, and that sits on GitHub's pages, not in anyone's forecast.
Copilot Fusion pages and changelog to re-check
Watch three things on GitHub's Copilot Fusion page and changelog. They are the pricing wording, the list of plans that can use it, and any mention of an API, webhook, or Actions integration.
If pricing changes, your cost per run changes with it. If the plans change, so does whether your team can use it at all.
A named trigger or action is what lets a workflow call Fusion without someone opening an editor. Note the date you last read each one, so a quiet edit shows up as a difference rather than a hunch.
Pick a job where a wrong answer costs you a retry, not an incident. Then work in this order:
- Read GitHub's Fusion page in full, and write down only what it states, not what you infer.
- Check whether your current Copilot plan is eligible, and who on the account can enable it.
- Connect Fusion to one low-risk workflow, such as drafting a summary on a pull request, with a human reviewing the output.
- Measure your own cost and time per run against the assistant you use now, using the timestamps from the previous section.
If step 2 fails or step 3 needs a manual hand-off, that's your answer for now. Recheck the pages above and run the same four steps again when they change, so the process repeats whenever pages are updated.
Frequently asked questions
Those rechecks matter most for four questions the body leaves open, and each answer below says whether GitHub's page settles it.
Cost and availability
Is GitHub Copilot Fusion free? GitHub's page doesn't state this. It gives no price and no free-tier terms that I can cite, so don't budget for it or assume a free trial. Check the page again before you commit anyone's time to a pilot.
Who can use GitHub Copilot Fusion today? GitHub's page doesn't state this in a form you can plan around. Fusion is new as of 2026-10-31, and the page doesn't spell out which plans, organizations, or accounts get access.
Until it does, treat availability as unconfirmed for your team, and confirm it by checking whether the feature appears in your own GitHub settings.
Automation and sources
Can I use GitHub Copilot Fusion in an automated workflow? GitHub's page doesn't state this. It names no API, no trigger, no action, and no rate limits, which are the details that decide whether a workflow can call Fusion at all.
Without them, you can only use Fusion by hand, inside GitHub's own interface. Wait for a documented endpoint before you wire it into anything that has to run unattended.
Where do I find GitHub's official Fusion information? GitHub's own Fusion page is the source, and it's the one this article judged.
Treat anything outside GitHub's pages, including summaries like this one, as secondhand. When a vendor page is silent on something, the right answer is "not stated," not a guess.
Related reading
Running the numbers
See what the same workload costs here.
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