Same seven criteria for every tool · checked November 2026

The best CI tools, compared side by side

GitHub Actions, GitLab CI/CD, CircleCI, Buildkite, Jenkins and the runner layers that speed up Actions, on speed, cost model, setup effort and fit. Every claim links to its source.

Best CI tools compared

Filter by what you decide on. How each criterion is defined, and how to test a tool on your own workload: How we compare CI tools.

8 of 8 tools
Every row links to its sources: the vendor’s own documentation and pricing pages. Prices and limits change; check the linked page before you buy.
ToolSpeed leversCost modelSetup effortBest fitWhat you give upSources
Graphide CI
Runner layer for GitHub Actions
First pick on GitHub Actions		Caches already on the runner when the job starts; the tests a change can reach, split across as many runners as it takes. When reachability is unclear it runs more tests, never fewer.Pay as you go per vCPU-minute, $20 monthly minimum; Enterprise priced per team.Low: one pull request that changes each x64 Linux job's runs-on to graphide.Teams on GitHub Actions, in a GitHub organization, waiting on x64 Linux build and test jobs. Strongest where agents push many changes a day.Runs x64 Linux jobs only; macOS, Windows, Arm and self-hosted jobs stay where they are. Needs a GitHub organization.
GitHub Actions
CI/CD built into GitHub		Hosted runners in standard and larger sizes; actions/cache restores caches over the network each job; matrix jobs for parallelism. Test splitting and selection are yours to build.Free on public repositories with standard runners; private repositories get minutes included in the plan, then per-minute billing.Low if your code is on GitHub: add a file under .github/workflows.Teams whose code is on GitHub and who want CI with nothing else to sign up for.Speed is whatever the runner and a network cache restore give you; no test selection; minutes grow with change volume.
GitLab CI/CD
CI/CD built into GitLab		cache: and artifacts keywords; parallel: and parallel:matrix to fan out jobs; needs: to run jobs as soon as their inputs are ready.Per-seat GitLab tiers with compute minutes included on GitLab-hosted runners; your own runners use your own machines.Low if your code is on GitLab; medium to high if it means moving repositories off GitHub.Teams whose code and reviews already live in GitLab, or who need a self-managed GitLab.Tied to GitLab: coming from GitHub means moving or mirroring repositories and rewriting workflows.
CircleCI
Hosted CI platform		save_cache/restore_cache and Docker layer caching; the parallelism key with circleci tests split splits a suite by past timings.Credit-based: plans include credits, jobs spend credits per minute by executor size. Free plan available.Medium: connect the repository and rewrite workflows in CircleCI's config.Teams that want hosted CI with test splitting built in and executors for Linux, macOS, Windows, Arm and GPU.A second system beside your code host, and a config to rewrite from GitHub Actions.
Buildkite
CI control plane, bring your own agents		As fast as the machines you give it: long-lived agents keep warm state; hosted agents add cache volumes on local disks. Dynamic pipelines decide steps at runtime.Plans priced per user, plus your own compute for self-hosted agents or vCPU-minutes for hosted agents.High for self-hosted agents (you run and scale the fleet); medium on hosted agents.Larger teams with a platform group, big monorepos, or jobs that must run on their own hardware.You operate the agent fleet, its autoscaling and its images, unless you pay for hosted agents.
Jenkins
Open-source automation server you host		Whatever your agents give: persistent workspaces keep state between builds; parallel stages split work across agents you add.Free open-source software; you pay for the servers and the people who maintain them.High: install and patch the controller, plugins and agents.Teams that must run everything on their own network, or already have Jenkins and people who know it.Ongoing maintenance: controller upgrades, plugin compatibility and security advisories are yours.
Depot
Runner layer for GitHub Actions		Faster machines and Depot Cache behind actions/cache with no job changes; Docker builds run next to the runner if you use Depot's builders.Monthly plans with included minutes, then per minute, tracked by the second.Low: change runs-on to a Depot label, such as depot-ubuntu-24.04.Teams on GitHub Actions who want faster runners across Linux, Windows and macOS, and faster Docker image builds.Runs every test your workflow runs; no selection by change. Actions runners need a GitHub organization.
Blacksmith
Runner layer for GitHub Actions		Colocated cache behind actions/cache and popular cache actions; Docker layer reuse through Blacksmith's build actions.Usage-based per runner minute. Check blacksmith.sh/pricing for current rates and free allowance.Low: a migration wizard rewrites runs-on labels, such as blacksmith-2vcpu-ubuntu-2404.Teams on GitHub Actions who want faster runners and better visibility into runs, logs and flaky tests.Runs every test your workflow runs; no selection by change. Needs a GitHub organization.

Each tool on the seven criteria

Push-to-verdict time, caching, parallelism, pricing model, migration effort, security and agent-heavy workloads. No ratings or scores: speed depends on your workload, so measure it with the benchmark.

Graphide CI · Runner layer for GitHub Actions

Your existing GitHub Actions jobs run on Graphide's runners with warm caches, tests split across runners, and each change running the tests it can reach. A failing test still fails the job.

Push-to-verdict time
Shortens the wait three ways: warm dependency and build caches, tests split across runners, and each change running only the tests it can reach. The verdict does not change: a failing test always fails the job, and GitHub decides pass or fail from the job's own steps.
Caching
Dependencies and build caches are already on the runner when the job starts, so a job does not spend its first minutes restoring them.
Parallelism
The tests a change reaches are split across as many runners as it takes, without you writing the split. Graphide traces which test reaches which function; when it cannot tell, it runs more tests, never fewer.
Pricing model
Pay as you go: $0.003 per vCPU-minute, billed by the second, with a $20 monthly minimum and a monthly cap you set. Enterprise is custom. Free trial per org. Check graphide.com/pricing for current terms.
Migration effort
Your workflows stay on GitHub Actions. Switching opens one pull request that changes each x64 Linux job's runs-on line to graphide and nothing else. Switching back opens the reverse pull request.
Security
Each job runs in its own fresh micro-VM, destroyed when the job ends; machines cannot reach each other; fork jobs are moved off hosts running trusted jobs. GitHub hands each job its secrets as on its own runners.
Agent-heavy workloads
Built for teams where agents write most of the code: a coding agent can switch a repository through Graphide's MCP server, agent signals warm machines before a push lands, and running only reachable tests keeps test cost per change down as change volume rises.
Fits
The first thing to try if your team already runs GitHub Actions and the wait is x64 Linux build and test jobs: nothing to rewrite, the same pass/fail verdict, and a switch you can undo with one pull request.
Limits
  • Runs x64 Linux jobs. Jobs on macOS, Windows, Arm or your own runners keep running where they do today; the switch pull request lists them.
  • Needs a GitHub organization: its runners do not take jobs from a personal GitHub account.
  • Works on GitHub Actions workflows. It is not a separate CI platform for GitLab or Jenkins pipelines.
  • How much faster a job gets depends on the job. Measure it against your own baseline (see How we compare).

GitHub Actions · CI/CD built into GitHub

Workflows in YAML next to your code, run on GitHub-hosted or self-hosted runners. The default for code that lives on GitHub.

Push-to-verdict time
Set by the runner size you choose, how long caches take to restore, how long a job waits for a runner, and how many tests every change runs. GitHub publishes no general speed figure; measure your own.
Caching
The actions/cache action and the built-in caching of setup actions save and restore caches through GitHub's cache service. Storage per repository is limited; check GitHub's caching docs for the current limit and eviction rules.
Parallelism
Separate jobs run in parallel, and a matrix strategy fans one job out across versions or shards. How many jobs run at once depends on your plan. Splitting a test suite across shards is up to your workflow.
Pricing model
Free for public repositories on standard GitHub-hosted runners. Private repositories get an amount of minutes and storage included with the plan, then pay per minute; larger runners are always billed per minute. Check GitHub's Actions billing page for current rates.
Migration effort
Nothing to migrate if you are already here. Moving in from another CI means rewriting pipelines as workflows; GitHub's Actions Importer can convert some CircleCI, GitLab, Jenkins and other configs.
Security
Secrets at organization, repository and environment level; a scoped GITHUB_TOKEN per run; OpenID Connect to cloud providers instead of long-lived keys. Hosted runners are fresh for each job.
Agent-heavy workloads
Every push and pull request from an agent starts runs, so minutes, queue time and test cost scale with change volume. It fits agents that open pull requests on GitHub, but has no built-in way to run fewer tests per change.
Fits
The sensible default if your code is on GitHub. When the wait gets long, a runner layer such as Graphide CI speeds it up without leaving Actions.
Limits
  • Hosted runner jobs restore caches over the network and run every test the workflow names.
  • Concurrency, cache storage and included minutes depend on the plan: check the docs before sizing a large team.

GitLab CI/CD · CI/CD built into GitLab

Pipelines in .gitlab-ci.yml, run on GitLab-hosted runners or on GitLab Runner installed on your own machines.

Push-to-verdict time
Set by runner size, cache and artifact transfer, and how jobs are arranged in stages or with needs:. Measure on your own pipeline.
Caching
The cache: keyword stores files between jobs and pipelines; artifacts pass build output to later jobs. Where caches live depends on the runner's configuration.
Parallelism
parallel: runs one job as several copies, parallel:matrix fans out by variables, and needs: builds a graph so jobs start as soon as their dependencies finish.
Pricing model
GitLab tiers are priced per user, and GitLab.com includes compute minutes for its hosted runners by tier. Check GitLab's pricing and compute minutes pages for current amounts.
Migration effort
Coming from GitHub Actions: rewrite each workflow as .gitlab-ci.yml jobs, move secrets to CI/CD variables, and move or mirror the repository. GitLab publishes a migration guide from Actions.
Security
Masked and protected CI/CD variables, OpenID Connect tokens for cloud access, and the option to run every runner on your own network.
Agent-heavy workloads
Change volume lands on compute minutes or on your runner fleet. No built-in test selection; fewer tests per change is your pipeline's logic.
Fits
The natural choice when the team already works in GitLab. Rarely worth moving repositories for CI alone.
Limits
  • Best value only when the code is on GitLab.
  • Self-managed runners are yours to scale and patch.

CircleCI · Hosted CI platform

A CI service with its own config (.circleci/config.yml), reusable orbs, many executor types and built-in test splitting by timing.

Push-to-verdict time
Set by executor size, cache restores and how far the suite is split. Timing-based splitting helps long suites; measure it against your own baseline.
Caching
save_cache and restore_cache keyed by checksums of lockfiles; Docker layer caching for image builds; workspaces to pass files between jobs.
Parallelism
Set parallelism on a job and use circleci tests split --split-by=timings to divide tests across copies using stored test timings.
Pricing model
Usage in credits: each executor size spends a set number of credits per minute, and plans include an amount of credits. Check circleci.com/pricing for current plans.
Migration effort
From GitHub Actions: rewrite workflows as jobs and workflows in config.yml, replace actions with orbs or scripts, and move secrets to contexts or project settings.
Security
Contexts to scope secrets to groups, OpenID Connect tokens, IP ranges on some plans, and self-hosted runners for jobs that must stay on your network.
Agent-heavy workloads
Credits scale with change volume. Timing-based splitting shortens the wait for each change but still runs the whole suite.
Fits
A good fit for teams that want hosted CI outside GitHub with test splitting built in, especially across many platforms.
Limits
  • Every workflow is rewritten in CircleCI's config to move in.
  • Runs the full suite per change unless you build selection yourself.

Buildkite · CI control plane, bring your own agents

Buildkite runs the pipelines, UI and scheduling; the agents that run jobs run on your machines, or on Buildkite's hosted agents.

Push-to-verdict time
Depends on your agents: machine size, how warm they are, and how fast your fleet scales up for a burst of pushes. Dynamic pipelines let a change generate only the steps it needs.
Caching
On your own agents, anything the machine keeps between jobs. On hosted agents, cache volumes on local NVMe disks and Git mirroring.
Parallelism
The parallelism attribute runs a step as many copies; the number of agents you run sets the ceiling. Buildkite's Test Engine can split tests by timing.
Pricing model
Plans are priced per user. Self-hosted agents run on compute you pay your cloud for; hosted agents are billed in vCPU-minutes. Check buildkite.com/pricing for current plans.
Migration effort
From GitHub Actions: rewrite workflows as pipeline steps, stand up agents (or hosted queues), and move secrets to your secrets store or Buildkite secrets.
Security
With self-hosted agents, source code, secrets and build output stay on your machines. Signed pipelines verify steps on self-hosted agents (not supported on hosted agents).
Agent-heavy workloads
Scales as far as your fleet does; a burst of agent-written pushes is a capacity-planning problem you own. Dynamic pipelines can cut steps per change if you write the logic.
Fits
The pick for teams that want control of the machines and have people to run them.
Limits
  • Self-hosted agents mean maintaining machines, images and autoscaling.
  • Signed pipeline validation is not supported on hosted agents.

Jenkins · Open-source automation server you host

Free, self-hosted and extended by plugins. Pipelines in a Jenkinsfile; agents are machines you run.

Push-to-verdict time
Set by agent hardware, workspace reuse and how stages are split. Long-lived agents can be fast; queues grow when agents run out.
Caching
Workspaces on persistent agents keep dependencies between builds; beyond that, caching comes from plugins or your own scripts.
Parallelism
parallel blocks in a Jenkinsfile run stages at once on the agents you have; scaling agents up and down is yours to set up (for example with cloud agent plugins).
Pricing model
Free software under the MIT licence. The cost is servers, storage and maintenance time.
Migration effort
From GitHub Actions: rewrite workflows as Jenkinsfiles, find plugins for what actions did, and stand up agents. Moving away from Jenkins is the more common direction.
Security
Everything stays on your network, and everything is yours to patch. Jenkins publishes security advisories for the core and plugins.
Agent-heavy workloads
More pushes mean more agents to run and more queue time when they run out. No built-in test selection.
Fits
Worth keeping where it already works and the team has the people to run it; rarely the first choice for a new team.
Limits
  • Maintenance load grows with plugins and agents.
  • No hosted option from the project itself.

Depot · Runner layer for GitHub Actions

Drop-in GitHub Actions runners on ephemeral single-tenant machines with Depot's cache, alongside its remote Docker builds.

Push-to-verdict time
Shorter through faster hardware and faster cache transfers. Depot publishes its own speed claims; measure them on your jobs.
Caching
Runners use Depot Cache for the GitHub Actions cache with no change to your jobs; cache is scoped by repository and not isolated by branch.
Parallelism
Depot states no concurrency limits. Splitting tests across jobs is still your workflow's matrix.
Pricing model
Plans include a number of runner minutes and cache storage, with per-minute billing after; larger runners use minutes faster. Check depot.dev/pricing for current plans.
Migration effort
Change each job's runs-on label to a Depot label after connecting your GitHub organization.
Security
Each job runs on an ephemeral single-tenant EC2 instance that is never reused; runners can run in your own AWS account; egress filtering is available.
Agent-heavy workloads
Each change runs faster, but it still runs the whole workflow, so test cost scales with change volume.
Fits
A strong pick when the slow part is hardware, cache transfer or Docker builds, including on macOS and Windows.
Limits
  • No test selection: the workflow decides what runs.
  • Depot's Actions runners support repositories owned by GitHub organizations.

Blacksmith · Runner layer for GitHub Actions

Drop-in GitHub Actions runners with a colocated cache for the standard cache actions, Docker layer caching and CI observability.

Push-to-verdict time
Shorter through its machines and colocated cache. Blacksmith publishes its own speed claims; measure them on your jobs.
Caching
The official and popular third-party cache actions use Blacksmith's colocated cache instead of GitHub's backend; Docker layer caching through its own setup and build actions.
Parallelism
Your workflow's own jobs and matrix run on Blacksmith machines; its Test Analytics shows failures and slow tests. Check its docs for concurrency limits.
Pricing model
Billed by usage per runner size. Check blacksmith.sh/pricing for current rates.
Migration effort
Install its GitHub integration, then use the migration wizard or change runs-on labels by hand; swap Docker build actions for its own to get layer caching.
Security
Jobs run on Blacksmith's infrastructure; see its documentation for isolation and network allowlisting.
Agent-heavy workloads
Each change runs faster, but runs the whole workflow, so test cost scales with change volume.
Fits
A good pick when you want faster Actions runners and better debugging tools in one place.
Limits
  • No test selection: the workflow decides what runs.
  • Limited to GitHub organizations, not personal repositories.

Head-to-head comparisons

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