Most engineering teams don't choose between GitHub and GitLab by running a formal evaluation. They choose because someone senior used one of them at a previous job, or because a new project needs to go somewhere and nobody wants to spend a week debating it. That's a reasonable way to make a low-stakes decision, and a riskier way to make this one. Once a team's repositories, CI pipelines, issue history, and access permissions live on a platform, moving them later is disruptive. Most teams just don't do it, even after the original reasoning stops applying to how the team actually works.
So the real question isn't "which platform is better." It's narrower, and easier to answer: given your team's size, compliance needs, CI/CD volume, and how much of your workflow you want living in one product versus stitched together from several, which platform's default tradeoffs cost you less over time? This guide works through that question using each platform's own documentation and pricing pages, and ends with a framework for working out the answer for your own situation rather than a generic recommendation.
Git, GitHub, and GitLab are three different things
It's worth clearing up a distinction that trips up developers at every experience level. Git is the version control system that runs on your own machine. It tracks every change to your files and lets you branch, rewind, and merge those changes back together. (If branching is still new to you, our beginner's guide to Git branching covers it step by step.) Git doesn't require GitHub or GitLab at all. You can use it entirely locally and never touch either platform.
GitHub and GitLab are hosting platforms built on top of Git. They exist for the moment you need to collaborate with someone else, back your code up somewhere off your laptop, or automate testing and deployment. Git is the underlying protocol. GitHub and GitLab are two different products built around it, with real differences in philosophy and not just cosmetic differences in interface. (For more on how Git and GitHub specifically relate to each other, see Git vs GitHub: What's Actually the Difference.)
The short version: GitHub is built as a hub with a large marketplace of third-party integrations. GitLab is built as one product that tries to cover the whole software delivery lifecycle without requiring separate tools. Neither approach is objectively correct. Which one costs you less depends on how your team already works.
The core philosophy difference, and why it changes daily workflow
GitHub's ecosystem assumes developers want to select best-in-class tools and connect them. GitHub Actions has a large marketplace of community-built workflows that can be dropped into a pipeline with a few lines of YAML: deployment actions, linting actions, notification actions, and so on.
GitLab takes a more consolidated approach. Planning, source control, CI/CD, security scanning, a container registry, and deployment tracking are built into one application with a shared data model, rather than assembled from separate products.
This distinction shows up in ordinary day-to-day work. On GitHub, security scanning is split between GitHub's own paid add-ons (Secret Protection and Code Security) and third-party tools such as Snyk, each reporting into its own interface. On GitLab, the scanners run as jobs in the same pipeline, and with the Ultimate tier their findings appear directly in the merge request that introduced them, in the interface developers already have open.
What "shared data model" means in practice
When security findings, pipelines, and deployments live in one system, GitLab's AI layer can draw on all of that context together. GitLab's Duo Agent Platform is built around that idea: agents that work across planning, code review, security, and pipelines rather than just the editor.
GitHub's AI is organized differently. Copilot spans code, issues, and pull requests, and GitHub's own security products are native to the platform. For example, Copilot Autofix proposes fixes for code scanning alerts. Findings from third-party scanners reach GitHub through integrations such as SARIF uploads and status checks. So the gap is smaller if you stay inside GitHub's own security products, and larger if your security stack is a mix of outside vendors.
This is a genuine structural difference, not a case where one approach is better in the abstract. A team that already prefers assembling specialized tools will find GitHub's model natural. A team that would rather avoid managing several vendor relationships for one pipeline will find GitLab's model saves real coordination overhead.
A note on mixed setups: plenty of organizations run both platforms simultaneously. They keep open-source or community-facing repositories on GitHub, where contributors already have accounts, and internal or proprietary code on GitLab for tighter self-hosting and compliance control. There's no requirement to standardize on exactly one.
CI/CD: the comparison that decides most real choices
CI/CD tooling is frequently the deciding factor in this comparison, so it's worth being concrete about what each platform's syntax looks like. Both examples below run the same job on the same triggers: every pull or merge request, and every push to the main branch.
A basic GitHub Actions workflow, stored in .github/workflows/:
name: Run Tests
on:
push:
branches: [main]
pull_request:
branches: [main]
jobs:
test:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v5
- uses: actions/setup-node@v5
with:
node-version: 'lts/*'
- run: npm ci
- run: npm testA comparable pipeline in GitLab CI, defined in a single .gitlab-ci.yml file at the repository root:
stages:
- test
run_tests:
stage: test
image: node:lts
script:
- npm ci
- npm test
rules:
- if: $CI_PIPELINE_SOURCE == "merge_request_event"
- if: $CI_COMMIT_BRANCH == $CI_DEFAULT_BRANCHFunctionally these accomplish nearly the same thing, but the structure differs. GitHub's version relies on reusable community actions (actions/checkout and actions/setup-node) that someone else builds and maintains. GitLab's version points directly at a Docker image and runs commands against it, with no marketplace dependency required. Teams that like composing pipelines from prebuilt pieces will generally find GitHub's ecosystem faster to work in. Teams that prefer writing exactly what runs, without an abstraction layer, will find GitLab's plain YAML more direct. Neither structure is objectively cleaner. It's a style preference with real workflow consequences either way.
Two practical notes on these examples. In real projects, pin a specific Node version instead of "latest LTS" so builds stay reproducible, and check each action's page for its current major version. And the rules block in the GitLab file matters more than it looks: triggering on both push events and merge request events for the same branch is a common way to end up with duplicate pipelines, which burn compute minutes twice.
CI minutes: where budgets actually get affected
Free-tier CI minutes look generous until a test suite grows and pull request volume increases. The table below uses figures from GitHub's pricing page, GitHub's Actions billing docs, GitLab's pricing page, and GitLab's compute minutes docs.
| Item | GitHub | GitLab |
|---|---|---|
| Free tier, private repos | 2,000 minutes/month (public repos are free) | 400 compute minutes/month per top-level group |
| Entry paid plan | Team: 3,000 minutes/month | Premium: 10,000 compute minutes/month, a flat pool per top-level group rather than per user |
| Top plan | Enterprise: 50,000 minutes/month | Ultimate: 50,000 compute minutes/month |
| Overage, standard Linux runner | $0.006/min (2-core, rates revised January 1, 2026) | $10 per 1,000 compute minutes ($0.01/min) for the default small Linux runner |
| Windows runners | $0.010/min | Cost factor 1 (listed as beta in GitLab's docs) |
| macOS runners | $0.062/min | Cost factor 6 for the M1 runner (listed as beta in GitLab's docs) |
| Self-hosted runners | Free. GitHub's docs state that usage is free for self-hosted runners | Free on every plan, and they don't consume compute minutes |
| When you hit the limit | Spending defaults to a $0 budget, so jobs stop until the month resets or you raise it | Buy more minutes, upgrade, or move jobs to your own runners. The Free tier asks for a card to verify shared-runner use |
A worked example: what 1,000 build minutes cost on each platform
GitLab does apply an operating-system multiplier on its hosted runners. Its "cost factor" scales how many compute minutes a job uses, depending on runner type and size. The result is closer than most comparisons suggest. Assume you've already used up your included minutes and every job is billed at overage rates:
| 1,000 minutes of job time on... | GitHub | GitLab |
|---|---|---|
| Linux (standard runner) | $6.00 | $10.00 |
| Windows | $10.00 | $10.00 (beta) |
| macOS | $62.00 | About $60.00 (6,000 compute minutes at $0.01, beta) |
Runner specifications aren't identical across the two platforms, and larger runners cost more on both, so read this as a rough guide rather than a quote. Still, it overturns a common claim. GitHub is cheaper per Linux minute. On macOS, the two platforms end up close at overage rates. Where macOS and Windows jobs do hurt is the included minute pool, because those jobs drain it faster on both platforms. Mobile teams should model their own build mix in GitHub's pricing calculator and against GitLab's cost factors before assuming either platform is cheaper.
Seat prices usually dominate the total anyway. Take a 10-person team using 8,000 Linux minutes a month. On GitHub Team, that's about $40 in seats at the promotional $4 rate, plus 5,000 overage minutes at $0.006 (about $30), roughly $70 a month. On GitLab Premium, it's $290 in seats at the $29 list price, with all 8,000 minutes inside the 10,000-minute pool, so about $290 a month. Neither number includes security or AI add-ons, which is where the comparison gets more interesting.
Self-hosting: a structural difference that settles the decision for some teams
This is arguably the single biggest structural difference between the two platforms, and it doesn't come up as often as it should outside of procurement conversations.
GitLab offers a Community Edition that is free, open-source, and can be run on infrastructure you control, with no licensing fee and no enterprise contract required to get started. It includes the core platform: source control, CI/CD, issue tracking, and merge requests. GitLab's self-managed Free tier also lets you bring your own storage and runners.
GitHub does not offer an equivalent. Self-hosting GitHub requires GitHub Enterprise Server, a paid enterprise product. There is no free, self-hostable version of GitHub. GitHub's own platform code is closed-source, distinct from the enormous amount of open-source code the platform hosts on behalf of others.
This matters most for organizations with hard constraints: regulated industries such as healthcare, finance, or government contracting, or air-gapped environments where code legally cannot leave the organization's own network. In those situations, GitLab's free self-hosted option is frequently the deciding factor before feature comparisons even come into play. It functions as a compliance requirement that only one of the two platforms can satisfy without an enterprise sales conversation. (If self-hosting is your only requirement, lighter open-source forges such as Gitea or Forgejo are also worth a look.)
For organizations without those constraints, this difference matters considerably less. GitHub Enterprise Cloud now offers data residency, which lets you choose a regional deployment so in-scope data is stored at rest in a designated location. GitHub's pricing page lists the EU and Australia as available regions, with more planned, so check that your region is covered. On the GitLab side, GitLab.com is currently hosted in the United States, while GitLab Dedicated, a single-tenant SaaS offering, lets you pick a region. For teams that want maximum control over where code physically resides, GitLab's self-managed Community Edition remains the more accessible route.
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Security features: a closer comparison than it first appears
This is the category where the two platforms differ most in pricing model, though the feature gap is narrower than many comparisons claim.
GitHub
- Free on every plan: Dependabot alerts and security and version updates, even on private repositories.
- Free on public repositories only: secret scanning, push protection, and code scanning with CodeQL.
- For private repositories: two separate add-ons, GitHub Secret Protection ($19 per active committer per month) and GitHub Code Security ($30 per active committer per month). Both can be bought on the Team plan without upgrading to Enterprise. Code Security also adds the dependency review action and Dependabot auto-triage rules.
Prices are from GitHub's announcement of the two products. Confirm current rates on GitHub's Advanced Security page. Buying both for full coverage adds $49 per active committer per month at list price, on top of the base plan.
GitLab
- All tiers: basic SAST, Secret Detection, and Container Scanning can run in every plan, including Free.
- Free and Premium: those scans only output results as JSON artifact files, per GitLab's pricing FAQ.
- Ultimate: new findings show up in merge requests and pipelines, vulnerabilities are tracked over time in a vulnerability report, and the tier adds dependency scanning, DAST, advanced SAST, security policies, and compliance tooling.
That last point corrects a common shortcut. GitLab's integrated security experience isn't bundled into the mid-tier. It lives in Ultimate, which GitLab prices through its sales team.
So where is the real difference?
Both platforms put the polished, in-context security experience behind extra spend. The difference is how you pay. GitHub sells it as a modular, per-active-committer add-on on top of a cheap seat. GitLab sells it as a higher tier with custom pricing, which also bundles compliance, portfolio planning, and the larger CI pool. A team that only needs secret scanning can buy exactly that on GitHub. A team that wants one vendor and one contract for the whole security and compliance picture may find GitLab Ultimate simpler to procure, though not necessarily cheaper.
Compliance follows a similar pattern. Both vendors publish third-party audit reports such as SOC 2, and each maintains a trust center with current attestations. GitLab's Ultimate tier bundles compliance frameworks and dashboards into the product, while GitHub's compliance story often involves combining Enterprise features with the security add-ons. Teams that spend meaningful time each quarter assembling compliance evidence for auditors should price this out for their specific situation, since the difference compounds every year spent on a workflow that doesn't fit.
AI features: Copilot and Duo
Both platforms have invested heavily in AI assistants, and the way each built theirs mirrors the philosophical split described earlier.
GitHub Copilot is embedded directly in the coding experience: inline suggestions, chat, IDE integration, and CLI integration, plus a coding agent that can work on issues and open pull requests. GitHub's Agent HQ adds a "mission control" view for assigning and tracking several agents in parallel, including agents from providers other than Copilot, though availability of specific third-party agents depends on your Copilot plan. Copilot is sold separately from the base GitHub plan.
GitLab Duo takes a broader DevSecOps-lifecycle approach. The Duo Agent Platform became generally available in January 2026 for Premium and Ultimate. It covers merge request reviews, pipeline troubleshooting, security analysis, and custom multi-step flows, and it integrates external agents such as Claude Code and Codex CLI. Usage is metered in GitLab Credits. Premium and Ultimate subscriptions include $12 and $24 of credits per user per month, which GitLab describes as a limited-time promotional allowance. Beyond that, credits cost $1 each, and on the Free tier AI features require purchasing credits.
The general tradeoff: for a small, fast-moving team focused mainly on shipping code, Copilot's code-suggestion quality is strong and tends to translate into day-to-day speed. For a larger organization where code quality, security posture, and compliance across many developers matter as much as raw output speed, Duo's ability to reason across the full pipeline, not just the code, can deliver more value relative to cost. AI assistant quality and pricing are among the fastest-moving areas of both platforms, so check current capabilities and reviews rather than relying only on this description.
What "shared context" looks like in practice
Below is a simple interactive comparison. Click each tab to see, side by side, roughly what a developer encounters when a pull or merge request updates a dependency that has a known vulnerability, depending on the platform and plan.
gl-sast-report.json). The merge request shows no security widget.This illustrates the philosophical difference in a small, concrete form, and it shows why the plan matters as much as the platform. On either side, the in-context security view sits behind a paid add-on (GitHub Code Security) or the top tier (GitLab Ultimate). The difference is that GitLab's scanners, pipeline, and merge request share one system, while on GitHub the same experience is assembled from GitHub's own add-ons plus whatever third-party tools you connect. It's a small interface difference with a real operational consequence at scale. This mockup is illustrative rather than a screenshot of either platform's live interface, and both interfaces evolve over time.
Beginner-friendliness: an underweighted but real factor
For teams hiring junior developers or bootcamp graduates, or building a team where onboarding speed matters, this deserves more weight than it typically gets in comparison content.
GitHub is where most beginner tutorials point by default. Searching how to deploy a given type of application frequently ends with instructions to push it to GitHub, and the surrounding ecosystem (Stack Overflow answers, forum threads, video walkthroughs) defaults to GitHub's interface and terminology. This gives new hires a head start on muscle memory and troubleshooting.
GitLab's interface has more built-in surface area (more panels, more settings) because it's trying to serve as a full DevOps platform in one screen. That's a strength once a team knows the platform well, and a real onboarding speed bump for someone new to it. This isn't a design flaw. Doing more in one place inherently means more to learn on day one.
Practical tip for mixed-experience teams: don't force everyone through an identical onboarding ramp. Let newer developers get comfortable with core Git commands and pull or merge requests first, and treat platform-specific features as a separate, later lesson. Git fundamentals transfer completely between platforms. Interface-specific quirks don't, but they're the easier part to pick up once the fundamentals are solid.
Pricing at a glance
Pricing on both platforms moves. Plan structures, add-on splits, and included allowances have all changed materially within the past two years. Treat the summary below as a snapshot, not a quote, and check the current, official pages before making a purchasing decision: GitHub's pricing page and GitLab's pricing page.
| Plan | Price | Worth knowing |
|---|---|---|
| GitHub Free | $0 | Unlimited public and private repositories, Dependabot updates, Issues and Projects |
| GitHub Team | $4/user/month (promotional rate for the first 12 months) | Repository rules, code owners, required reviewers, multiple reviewers on pull requests |
| GitHub Enterprise | From $21/user/month (promotional rate for the first 12 months) | SAML SSO, audit log API, data residency on Enterprise Cloud, self-hosting through Enterprise Server |
| GitLab Free | $0 | Capped at 5 users in a private top-level group on GitLab.com, 10 GiB storage per project |
| GitLab Premium | $29/user/month, billed annually (list price; the page also offers a sales conversation) | Unlimited users, advanced CI/CD, 500 GiB per project, Duo Agent Platform access with promotional credits |
| GitLab Ultimate | Custom pricing through sales | In-context security findings, vulnerability management, compliance and governance, 50,000 compute minutes |
On top of the base plans, keep these add-ons in mind:
- GitHub Secret Protection and Code Security: $19 and $30 per active committer per month, respectively.
- GitHub Copilot: sold separately from the base plan, with its own tiers.
- GitLab compute minutes: $10 per 1,000 minutes, a one-time purchase.
- GitLab storage: $5 per month for 10 GiB, billed annually, on Premium and Ultimate.
- GitLab Credits: $1 per credit for on-demand AI usage beyond the included allowance.
The general pattern that emerges from comparing the two: GitHub's entry-level pricing is lower and its free tier is more generous on CI minutes, which is a large part of why it remains the default choice for solo developers, small teams, and open-source projects. GitLab's per-seat pricing is higher, but some of what that price includes (a larger shared CI pool, advanced CI/CD features, AI credits, and at Ultimate the security and compliance tooling) would otherwise be separate line items on the GitHub side. Once those costs are added back in for a GitHub-based setup that needs equivalent security coverage, the total cost gap between the two platforms is often narrower than the sticker prices alone suggest. Exactly how much narrower depends heavily on team size, CI volume, and which add-ons you need, and it can't be settled without a quote for GitLab Ultimate.
A framework for deciding
Rather than a simple checklist, it helps to work through these questions roughly in order, since each one can settle the decision on its own before you need to weigh the others.
- Is there a hard compliance or data-residency requirement? If code legally cannot leave your network (regulated industries, government contracting, air-gapped environments), GitLab's free self-managed Community Edition is likely to be the deciding factor by itself, with GitHub Enterprise Server as the paid alternative. If you only need data to stay in a region, compare GitHub Enterprise Cloud's data residency regions and GitLab Dedicated.
- What does your actual CI/CD volume and OS mix look like? Estimate your monthly build minutes and how much of that runs on Windows or macOS versus Linux. Run those numbers against both platforms' current published rates rather than relying on general guidance, since cost factors and per-minute rates can shift the total meaningfully depending on your specific mix. If you can run your own runners, remember that self-hosted usage is free on both platforms.
- Do you need security findings inside every pull or merge request, and from day one? If so, price GitLab Ultimate against GitHub Team or Enterprise plus Secret Protection and Code Security, using real quotes and your actual active-committer count. If you're comfortable choosing tools individually, or only need secret scanning, GitHub's modular model may fit better.
- How much does ecosystem and hiring familiarity matter to you? If you're hiring junior developers or leaning on the broadest possible community documentation, GitHub's larger tutorial and troubleshooting ecosystem is a real, if hard-to-quantify, advantage.
- Would running both platforms actually serve you better than picking one? Many organizations use GitHub for public-facing or community-driven repositories and GitLab for internal, security-sensitive infrastructure. This isn't a compromise position. It's a legitimate answer once an organization is large enough that the two use cases have genuinely different requirements.
If you work through these in order and still don't have a clear answer, that's a reasonable outcome. It usually means your team's requirements are genuinely balanced between the two platforms' strengths, and the deciding factor may end up being something specific to your organization (existing tooling, team preference, or a specific integration) rather than anything in a general comparison.
Frequently Asked Questions
Can I move my repositories from GitHub to GitLab, or the other way around?
Yes. GitLab has built-in import tooling for moving projects from GitHub, Bitbucket, and most other providers, and it can bring over more than just code, such as issues and merge requests. GitHub also offers importers for bringing repositories in, so check its current documentation for the sources it supports. For a full migration, a few general principles tend to hold regardless of platform: audit what needs to move rather than migrating everything, run the platform's built-in importer before writing custom scripts, rewrite CI pipeline files by hand since GitHub Actions workflow files and .gitlab-ci.yml aren't directly interchangeable, test the new pipeline on a throwaway branch first, and migrate access permissions and team roles last. Migration complexity varies by repository size and how many integrations are in use, so check each platform's current migration docs before planning a timeline.
Is GitLab actually slower or more complicated to learn than GitHub?
GitLab has more surface area, which isn't the same as more complexity per feature. It packs more capability into one interface because it functions as a broader DevOps platform rather than source control alone. For someone who only needs to push code, open a merge request, and review changes, the learning curve is generally comparable to GitHub's. It tends to feel heavier once you dig into CI/CD configuration, security dashboards, and compliance settings, areas where GitHub also requires extra configuration or add-ons to reach comparable depth.
Do I need the top-tier plan just to get decent security scanning?
It depends on what "decent" means. On GitLab, basic SAST, secret detection, and container scanning run on every tier, but in Free and Premium they only produce JSON artifact files. Seeing findings inside merge requests, tracking vulnerabilities over time, and running dependency scanning or DAST requires Ultimate. On GitHub, Dependabot alerts are free everywhere, while code scanning and secret scanning on private repositories require the Code Security and Secret Protection add-ons, billed per active committer on top of the base plan. In both cases, the integrated experience costs extra, so price your actual team size before deciding which route is cheaper.
Which platform is better for a solo developer working on personal projects?
For most solo developers, GitHub tends to be the more practical default. Its free tier includes 2,000 CI minutes for private repositories versus GitLab's 400, the community and tutorial ecosystem is larger, and if a project is later open-sourced, it's already on the platform where contributors are most likely to look. GitLab's core strengths (compliance tooling, self-hosting, an integrated DevOps platform) matter most once you're working with a team or organization, and add comparatively little value to a solo project.
What happens if I go over my free CI minutes?
On GitHub, accounts with a payment method on file default to a $0 spending budget, so jobs stop running once the included quota is used rather than generating an unexpected bill, unless that budget has been explicitly raised. On GitLab, you can purchase additional compute minutes, upgrade your plan, or run jobs on your own runners, which don't draw against the compute-minute allowance on any plan. Check each platform's current billing documentation if this is a live concern for your team.
Does GitHub charge for self-hosted Actions runners?
Not at the time of writing. GitHub announced a $0.002-per-minute charge for self-hosted runners in private repositories in December 2025, then postponed it the next day to re-evaluate. It never took effect, and GitHub's billing documentation says self-hosted runner usage is free. You still pay for the machines themselves. Since GitHub only postponed the idea, check the current billing docs if self-hosted runners are central to your budget.
Is one platform meaningfully more secure than the other by default?
Both platforms are secure as hosting infrastructure, and that's generally not where the meaningful difference lies. The real difference is how security tooling is packaged and priced. GitHub sells scanning as modular add-ons billed per active committer. GitLab includes basic scanners in every tier and keeps the integrated, merge-request-level experience in Ultimate. Neither approach means code is inherently less safe on one platform than the other. It's a difference in what's included out of the box versus what requires additional setup or cost.
Can GitHub or GitLab be self-hosted for free?
GitLab can: the Community Edition is free and open source, and GitLab's self-managed Free tier covers the core platform. GitHub cannot. Self-hosting GitHub requires GitHub Enterprise Server, a paid product. If you need a free, self-hosted forge but not GitLab specifically, open-source alternatives such as Gitea and Forgejo exist.
Conclusion
There's no universally "better" platform here, only a better fit for a given team's size, budget, and compliance situation. GitHub tends to win on entry-level cost, per-minute CI pricing on Linux, ecosystem breadth, and onboarding familiarity. GitLab tends to win on self-hosting flexibility, a larger shared CI pool on its paid plans, and having fewer separate vendor relationships to manage, with its deepest built-in security and compliance tooling available at the Ultimate tier. Both of those statements come with real exceptions depending on team size and specific needs, which is why the framework above is a sequence of questions rather than a single recommendation.
Pricing and plan structures on both platforms have changed meaningfully within the past two years and will likely keep changing, as the self-hosted runner episode showed. Before committing to either platform long-term, verify the current figures directly against GitHub's and GitLab's official pricing pages.
