Compare GitHub Actions runners and CI platforms: StarSling vs GitHub-hosted, Depot, Blacksmith, WarpBuild, Buildkite, and Namespace
StarSling brings Adaptive Compute, agent-generated optimization PRs, CI skills, configurable Review Runners, and dedicated GPU Runners to GitHub Actions. Compare how those capabilities improve job execution, workflows, and code review against the tools your team is evaluating.
How StarSling worksStarSling combines fast runners with AI optimization PRs that improve the pipeline over time. Compare each provider's runner families, Docker build setup and optimization offering below. Buildkite and Jenkins are CI platforms with their own pipeline models; the runner providers keep GitHub Actions.
| Where StarSling leads | Where others also deliver | ||||||
|---|---|---|---|---|---|---|---|
| Tool | Adaptive Compute | AI optimization PRs | CI optimization skills | GitHub Actions support | Unlimited concurrency | Faster GitHub Actions runners | Agent-first CLI |
| StarSling | Yes | Yes | Yes | Yes | Yes | Yes | Yes |
| Namespace | No | No | No | No | Yes | Yes | |
| GitHub-hosted | No | No | No | Yes | No | No | Yes |
| Depot | No | No | No | Yes | Yes | Yes | Yes |
| Blacksmith | No | NoRunner right-sizing PRs | No | Yes | Yes | Yes | NoCLI for logs and metrics |
| WarpBuild | No | No | No | Yes | Yes | Yes | No |
| Buildkite | No | No | No | No | No | No | Yes |
| Jenkins | No | NoFailure auto-fix PRs (experimental) | No | Self-hosted | No | Yes | |
Where others offer more
| Tool | Runner families | Docker builds |
|---|---|---|
| StarSling | Linux only: Ubuntu 26.04 or 24.04 | No separate build service: Docker builds run in your workflow on faster hardware, and the agents open PRs that fix the build and cache steps |
| Namespace | Linux AMD64, Linux ARM64, Windows and macOS | Remote builders by default, with an in-runner local-cache option |
| GitHub-hosted | Linux, macOS, and Windows (hosted-runner reference, checked 2026-07-14) | Runs in your workflow on GitHub's shared hardware; layer caching only through BuildKit's GitHub Actions cache backend (type=gha), with no remote builder |
| Depot | Linux, macOS, and Windows | Remote BuildKit builders that run in the same private network as the runner, each with a persistent NVMe layer cache (50 GB, expandable). Depot Cache is a distinct product, a remote cache for GitHub Actions, Bazel, Go, Gradle, Turborepo and more |
| Blacksmith | Linux x64 and ARM and macOS, with Windows Server 2025 in public beta | Docker layer caches kept on per-Dockerfile sticky disks that persist between runs, billed per GB-month |
| WarpBuild | Linux x64 and ARM64, macOS, and Windows | Remote "Docker builders" with Buildx integration, each builder profile keeping a persistent layer cache, plus a WarpBuilds/cache action that is a drop-in for actions/cache@v4 |
| Buildkite | Agents you host yourself, on-premises or in the cloud, with Buildkite-hosted agents also offered | Remote Docker builders: docker build and Buildx commands on Buildkite-hosted agents are directed to dedicated external builder machines rather than built on the agent, a default Enterprise-plan feature |
| Jenkins | Agents on any operating system that supports Java, on nodes you provide or provision through cloud providers | Builds run on your agents, with build tools installed on each node directly or in a container such as Docker |
Real results from StarSling customer workflows
These are StarSling's published customer measurements, not benchmark claims about Depot, Blacksmith, WarpBuild, or GitHub-hosted runners. Each result links to the case study that explains the measurement window, source method, and caveats.
lower compute cost per run on Partcl's heaviest CI jobs
faster test suites at Mastra
faster E2E tests at Better Auth
- Better Auth: after migration and three agent PRs, E2E went from 2m 22s to 1m 04s and CI went from 1m 40s to 1m 02s.
- Mastra: agents opened nineteen PRs across sleeps, polling, Docker healthchecks, sharding, race fixes, and runner migration; Combined store Tests measured 29m 56s to 5m 06s in the post-migration window.
- Partcl: on a synthesis-bound CI workload, the agents shipped eight optimization PRs, cut heaviest-job compute cost 13x per run, and reduced p95 queue time from 9.5 minutes to 35 seconds.
Agent-generated PRs that optimize your CI
Pull Requests merged by customers. StarSling agents analyze and optimize your CI automatically.
Agent-first CLI for your CI
sling is the agent-first CLI for StarSling Runners: why a job failed, where the time went and what CI costs, and the skill teaches your agent to use it.
Agent skills that optimize your CI
Open source, one install, and they run on your machine: each skill reads your workflows and hands your coding agent the evidence to fix them.
Adaptive Compute
Sandbox Router sends every job to the fastest available sandbox, and Afterburner adds up to 25% more CPU and up to 50% more RAM to a running step at no extra cost. Up to 2.32x faster than GitHub-hosted runners.
StarSling vs GitHub Actions
StarSling upgrades GitHub Actions with [Adaptive Compute](/blog/adaptive-compute): Sandbox Router sends every job to the fastest available sandbox, and Afterburner adds up to 25% more CPU and up to 50% more RAM to a running step at no extra cost.
StarSling vs Depot for GitHub Actions
StarSling goes beyond Depot with [Adaptive Compute](/blog/adaptive-compute): Sandbox Router sends every job to the fastest available sandbox, and Afterburner adds up to 25% more CPU and up to 50% more RAM to a running step at no extra cost.
StarSling vs Blacksmith runners for GitHub Actions
StarSling goes beyond Blacksmith with [Adaptive Compute](/blog/adaptive-compute): Sandbox Router sends every job to the fastest available sandbox, and Afterburner adds up to 25% more CPU and up to 50% more RAM to a running step at no extra cost.
StarSling vs WarpBuild
StarSling goes beyond WarpBuild with [Adaptive Compute](/blog/adaptive-compute): Sandbox Router sends every job to the fastest available sandbox, and Afterburner adds up to 25% more CPU and up to 50% more RAM to a running step at no extra cost.
Buildkite vs GitHub Actions: where StarSling fits
For teams choosing GitHub Actions over Buildkite, StarSling accelerates CI with [Adaptive Compute](/blog/adaptive-compute): Sandbox Router sends every job to the fastest available sandbox, and Afterburner adds up to 25% more CPU and up to 50% more RAM to a running step at no extra cost.
GitHub Actions vs Jenkins: where StarSling fits
For teams moving from Jenkins to GitHub Actions, StarSling accelerates CI with [Adaptive Compute](/blog/adaptive-compute): Sandbox Router sends every job to the fastest available sandbox, and Afterburner adds up to 25% more CPU and up to 50% more RAM to a running step at no extra cost.
GitHub Actions vs GitLab CI/CD: comparison and migration
For teams moving from GitLab CI/CD to GitHub Actions, StarSling accelerates CI with [Adaptive Compute](/blog/adaptive-compute): Sandbox Router sends every job to the fastest available sandbox, and Afterburner adds up to 25% more CPU and up to 50% more RAM to a running step at no extra cost.
CircleCI vs GitHub Actions: migration and StarSling runners
For teams moving from CircleCI to GitHub Actions, StarSling accelerates CI with [Adaptive Compute](/blog/adaptive-compute): Sandbox Router sends every job to the fastest available sandbox, and Afterburner adds up to 25% more CPU and up to 50% more RAM to a running step at no extra cost.
StarSling vs Namespace runners for GitHub Actions
StarSling goes beyond Namespace with [Adaptive Compute](/blog/adaptive-compute): Sandbox Router sends every job to the fastest available sandbox, and Afterburner adds up to 25% more CPU and up to 50% more RAM to a running step at no extra cost.
StarSling vs RunsOn runners for GitHub Actions
StarSling goes beyond RunsOn with [Adaptive Compute](/blog/adaptive-compute): Sandbox Router sends every job to the fastest available sandbox, and Afterburner adds up to 25% more CPU and up to 50% more RAM to a running step at no extra cost.
StarSling vs Ubicloud runners for GitHub Actions
StarSling goes beyond Ubicloud with [Adaptive Compute](/blog/adaptive-compute): Sandbox Router sends every job to the fastest available sandbox, and Afterburner adds up to 25% more CPU and up to 50% more RAM to a running step at no extra cost.
Review Runners vs CodeRabbit for AI code review
Choose [StarSling Review Runners](/products/review-runners) over CodeRabbit when you want to own the reviewer: choose your model and provider key, define repo-native review skills and scripts, and run team-defined reviewers in your GitHub Actions workflow.
Depot vs Blacksmith for GitHub Actions
Both replace GitHub-hosted runners without changing your workflows beyond the runs-on label, and both keep a Docker layer cache between runs, so the real difference is what each attaches to the build. Depot runs remote BuildKit builders that run in the same private network as the runner, each with a persistent NVMe layer cache of 50 GB, expandable, plus Depot Cache, a separate remote cache for GitHub Actions, Bazel, Go, Gradle, Turborepo and more. Blacksmith keeps Docker layer caches on per-Dockerfile sticky disks that persist between runs and are billed per GB-month.
The runner families differ too. Depot offers Linux, macOS and Windows runner types; Blacksmith offers Linux x64 and ARM and macOS, with Windows Server 2025 in public beta. So the choice follows the bottleneck: if the slow part of the pipeline is docker build itself, the remote-builder model is what moves it; if the whole job is slow, a faster runner changes every step of it. Both make the pipeline you already have run faster. StarSling is the only vendor whose agents open optimization PRs across the whole workflow: caching, installs, test sharding and the critical path.
Which runner fits which bottleneck
Start from the part of the run that is actually slow. Time a few runs before switching anything: the bottleneck usually picks the tool.
- Jobs wait before they start. That is queue time, and it is a concurrency problem rather than a hardware one. Cut queue time on GitHub Actions covers how to measure it from the run trigger rather than from the job's own timestamps, which is where most measurements of it go wrong.
docker builddominates the run. A remote builder moves that build off the machine running the job. Depot, WarpBuild and Buildkite each offer one (Buildkite on its Enterprise plan), with the capabilities in the table above.- Install, test and package steps dominate. Every step runs on the runner, so this is the case a drop-in runner swap actually fixes: one
runs-onlabel, no workflow rewrite. - You need macOS or Windows. StarSling publishes Linux runners only. The runner-families column above summarizes the supported operating systems.
- You are leaving GitHub Actions altogether. That is a platform migration, and Buildkite and Jenkins are the entries in this table on that axis.
- The pipeline itself is the problem. No runner makes an unsharded test suite or a missing cache go away. StarSling's agents open pull requests that apply the GitHub Actions CI best practices, which is the column of this table only one row is marked in.
- Fast GitHub Actions
- GitHub Actions alternatives
- GitHub Actions pricing
- Self-hosted GitHub Actions runners
- GitHub Actions CI best practices
- How to run automated code review in GitHub Actions
- Levels of CI: every way to make GitHub Actions cheaper and faster
- Adaptive Compute: up to 2.32x faster than GitHub-hosted runners
- Install the /ci-speedup skill to fix slow GitHub Actions
- Install the /ci-score skill to improve your GitHub Actions setup
- Install the /ci-secure skill to close critical attack vectors in GitHub Actions
- StarSling Runners are now generally available (opens in new tab)
- Launch YC: StarSling Runners - Self-Driving CI (opens in new tab)
- StarSling docs (opens in new tab)
- ci-speedup skill source (open source, MIT) (opens in new tab)
- ci-score skill source (open source, MIT) (opens in new tab)
- ci-secure skill source (open source, MIT) (opens in new tab)
Which GitHub Actions runner is right for me?
If you want faster runs and a pipeline that keeps improving itself, StarSling combines fast drop-in runners with AI agents that open optimization PRs. If you only need raw runner speed, any fast-runner provider works; if your main bottleneck is Docker image builds, a build-acceleration tool like Depot fits.
Do these runners work with my existing GitHub Actions workflows?
Yes. StarSling and the other drop-in runners run your existing workflows; you switch by changing the runs-on label. StarSling's label is starsling-ubuntu-26.04.
What makes StarSling different from other fast runners?
StarSling adds AI agents that analyze your workflows, logs, and telemetry and open pull requests that optimize caching, dependency installs, parallelization, and test sharding, applying the GitHub Actions CI best practices an expert would by hand. Other runners make jobs faster; StarSling also improves the pipeline over time.
How does Buildkite compare to Depot for Docker builds?
Both move docker build off the machine running the job, but they sit at different layers. Buildkite is a hybrid CI/CD platform rather than a runner swap: a SaaS control plane that handles orchestration while you bring the compute, and on Buildkite-hosted agents docker build and Buildx commands are directed to dedicated external builder machines rather than built on the agent, a default Enterprise-plan feature. Depot stays inside GitHub Actions and attaches remote BuildKit builders that run in the same private network as the runner, each with a persistent NVMe layer cache (50 GB, expandable). So the practical question is whether you are replacing GitHub Actions or accelerating it. Neither opens optimization PRs against your workflow, which is the axis StarSling is on.
How does Buildkite compare to Blacksmith for CI runners?
They are not the same kind of product. Blacksmith is a drop-in GitHub Actions runner: you keep your existing workflows and change the runs-on label, and it offers Linux x64 and ARM and macOS runner families with Windows Server 2025 in public beta, keeping Docker layer caches on per-Dockerfile sticky disks that persist between runs, billed per GB-month. Buildkite replaces GitHub Actions altogether: the compute is agents you host yourself, on-premises or in the cloud, with Buildkite-hosted agents also offered. If the goal is faster GitHub Actions runs without rewriting your pipelines, that is the runner comparison; if it is moving off GitHub Actions entirely, it is a platform migration. Neither opens optimization PRs across the whole workflow, which is the axis StarSling is on.
How does WarpBuild compare to Blacksmith?
Both are drop-in GitHub Actions runners, so the difference is the runner families each offers and what each attaches to the Docker build. WarpBuild offers Linux x64 and ARM64, macOS, and Windows and pairs them with remote "Docker builders" with Buildx integration, each builder profile keeping a persistent layer cache and building natively for amd64 and arm64, plus a WarpBuilds/cache action that is a drop-in for actions/cache@v4. Blacksmith offers Linux x64 and ARM and macOS runner families up to 32 vCPU on Linux, with Windows Server 2025 in public beta, and keeps Docker layer caches on per-Dockerfile sticky disks that persist between runs, billed per GB-month. Blacksmith's [code]smith opens PRs that resize runners; neither has an agent that opens optimization PRs across the whole workflow, which is the axis StarSling is on.
Last updated 2026-10-29