Devin vs GitHub Copilot coding agent: which fits your team?

Devin and GitHub Copilot's coding agent are the two biggest names in background coding agents, and neither vendor will ever compare them for you. The short answer: pick by where your tickets live and how big the tasks run, because neither product takes your own key. So here's the Devin vs GitHub Copilot coding agent comparison from someone who is neither: what actually differs on triggers, execution, model lock-in, and price, and how to pick between them. We build Sinatra, a competitor to both, so every factual claim below links to the vendors' own docs, and our own product stays out of the way until the end.

Product details checked August 2026. Vendors change; check their docs for current specifics.

One naming note: GitHub's docs now call the product the Copilot cloud agent. Everyone still searches for "coding agent," so that's the name we'll use here.

Devin vs GitHub Copilot coding agent at a glance

	Devin (Cognition)	Copilot coding agent (GitHub)
Trigger	Web app, Slack, Linear, Jira, API, Devin Desktop	Assign the issue to Copilot, agents panel, @copilot on a PR, VS Code
Where code runs	Cognition's cloud workspaces, with an IDE you can open	Ephemeral GitHub Actions environment, 59-minute session cap
Repo access	Connect repos to Cognition's platform	Native; it works inside your existing GitHub org
Models	Cognition's own stack (SWE line, Fusion)	GitHub's model list (Claude, GPT families); Sonnet-class default
BYOK	No	No
Pricing	Free; Pro $20; Max $200; Teams $80 + $40/seat; enterprise ACUs	Paid Copilot plans from $10/mo; AI credits + Actions minutes
Network policy	Runs in Cognition's cloud	Default-on firewall with configurable allowlist
Enterprise posture	Services-led; FedRAMP High In-Process; partner network	Policy-led; org settings, existing GitHub Enterprise agreements

How you trigger them

Copilot's agent lives where GitHub work already happens. You assign an issue to Copilot, start a task from the agents panel, or mention @copilot in a PR comment, and it picks the work up with no new tool in the loop. If your team runs on GitHub Issues, the activation cost is close to zero.

Devin is trigger-rich by design. Sessions start from the web app, from Slack, from Jira tickets assigned to a Devin service account, from Linear, from an API call with a prompt, or from Devin Desktop, the Windsurf-derived editor that manages local and cloud agents from one view. That breadth is the point: Devin wants to be the agent layer across your whole toolchain, not a feature of one platform.

Where the code runs

A Copilot task runs in an ephemeral development environment powered by GitHub Actions: the agent explores the repo, makes changes, runs tests and linters, then opens a pull request, with a 59-minute cap per session. Outbound network access is limited by a firewall by default, with a recommended allowlist you can extend; blocked requests surface as warnings on the PR. The constraint cuts both ways: strong containment, but long-running work has to fit the window.

Devin sessions run in Cognition's cloud workspaces, each with its own interactive IDE that you can open mid-session and take over. Sessions are long-lived and parallel (up to 10 concurrent on the Free and Pro plans, unlimited above), which suits bigger, messier tasks that need hours rather than minutes. The tradeoff is that your code is executing on a third party's infrastructure rather than inside the CI platform you already vetted.

Models and lock-in

This is the cleanest philosophical split. Cognition is vertically integrated: Devin runs on Cognition's own model stack, the SWE line plus the Fusion architecture, with cost cuts passed down as the models improve. You don't pick the model, and you can't bring a key.

GitHub is a storefront: the coding agent offers a model picker drawn from GitHub's curated list, with a Claude Sonnet-class model as the default when admins haven't chosen, and even Claude and Codex agent variants on github.com. You get frontier-model choice within GitHub's menu, on GitHub's deprecation schedule, at GitHub's credit multipliers.

Neither agent supports bring-your-own-key. If routing work through your own Anthropic or OpenAI contract matters, both are out, and you're shopping a different list.

Pricing

Copilot's agent is a feature of the Copilot subscription: available on all paid plans, from Pro at $10 per month (with $15 in monthly AI credits) through Pro+ at $39 and Max at $100, plus Business and Enterprise seats. Agent sessions draw down AI credits based on the model and tokens used, and consume GitHub Actions minutes. Cheap to start; the variable is credit burn at volume.

Devin is priced as its own platform: Free, Pro at $20, Max at $200, Teams at $80 per month plus $40 per full seat, with usage metered through daily and weekly quotas and on-demand credits that roll over. Enterprise contracts bill in Agent Compute Units at a rate set in the order form. Neither vendor publishes a per-task price, so for both, the only trustworthy budgeting method is a pilot on your own tickets with the meter visible.

Enterprise posture

Devin sells like enterprise software: a Cognizant partnership to deploy across enterprise clients, FedRAMP High In-Process status for government, the Goldman Sachs pilot as the reference story, and a productivity guarantee backed by usage credits. If you want a vendor who shows up with services and a rollout plan, that's the shape of it.

Copilot's agent inherits GitHub's governance instead: admins enable it by policy, firewall and allowlist settings live in org settings, and procurement rides the GitHub Enterprise agreement you already signed. Nobody new gets access to your code, which for many security teams is the entire argument.

Choose Devin if, choose Copilot if

Choose Devin if the work is big: long-running tasks, legacy modernization, fleets of parallel sessions, triggers spread across Slack and Jira and Linear. Choose it too if you want one vendor accountable for the outcome, services included. It costs more and locks you into Cognition's stack, and in exchange you get the deepest platform in the category.

Choose Copilot's agent if your work already starts as GitHub issues and you want the shortest path from issue to PR: no new vendor, familiar billing, containment by default, and model choice within GitHub's menu. Its session cap and Actions-shaped environment favor small, well-scoped tickets over sprawling migrations, so match it to that kind of backlog.

And if neither fits: teams whose tickets live in Linear rather than GitHub Issues, or who want to bring their own keys instead of buying tokens through a platform, are the gap both products leave open. That's where Sinatra sits (assign the Linear issue, or add the Sinatra label to a GitHub issue), and we've compared the agents with real Linear support separately.

Common questions

Is Devin better than GitHub Copilot coding agent?

Neither dominates; they're optimized for different shapes of work. Devin is the deeper platform for long, parallel, enterprise-scale tasks; Copilot's agent is the lower-friction choice for turning well-scoped GitHub issues into PRs inside infrastructure you already trust. Pick by where your tickets live and how big the average task is.

Can I use my own API key with Devin or Copilot?

Not with either agent. Devin runs exclusively on Cognition's models, and the Copilot coding agent bills GitHub's hosted model menu through AI credits. If BYOK is a requirement, look at agents built around it instead.

Which is cheaper?

Copilot starts cheaper ($10 per month, agent included) and Devin's self-serve entry is $20, but entry price isn't the real number for either; both meter usage, through AI credits and Actions minutes on one side and quotas or ACUs on the other. Run the same ten tickets through each during a trial and compare what the meter says.

Can I run both?

Yes, and teams do: they're separate products with no integration conflict, since one lives in GitHub and the other in Cognition's platform. A common split is Copilot's agent for small repo-scoped fixes and Devin for larger delegated projects. The overhead is paying two meters and reviewing two agents' PRs.

If your loop starts with a Linear ticket and ends with a reviewed PR on your own model keys, that's the slice we build for. Start for free, or read the docs to see how the setup works.