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StarSling vs WarpBuild

StarSling is AI-native CI for GitHub Actions: drop-in Ubuntu runners plus agents that open optimization PRs for your workflows.

StarSling goes beyond WarpBuild with 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. Its agents deliver reviewable optimization PRs that improve your workflows, and its skills optimize CI speed, configuration, and security. Review Runners run code review agents you configure, while GPU Runners power GPU tests and model evaluations.

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Faster

StarSling Runners run your GitHub Actions jobs up to 2.32x faster than GitHub-hosted runners.

How StarSling works

Last updated 2026-10-29

Head to head

Benchmark build time (x64, 8 to 12 vCPU, p90 wait + job)
StarSlingRust 1m 54s, TypeScript 1m 07s (Sep 30 to Oct 4, 2026)
WarpBuildRust 2m 14s, TypeScript 1m 34s (Sep 30 to Oct 4, 2026)
Adaptive Compute
StarSlingYes. 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.
WarpBuildNo. One CPU and memory size per runner label.
Agent-generated PRs that optimize your CI
StarSlingYes. AI agents analyze logs/telemetry and open optimization PRs. See example PRs. CI harness with an agent loop.
WarpBuildNo. WarpBuild offers an MCP server for creating runners and images through its API. No agent that opens optimization PRs across the whole workflow.
Agent-first CLI for your CI
StarSlingYes. sling why diagnoses why a job failed, with evidence and next steps, and sling time decomposes CI wall-clock into runner-lifecycle phases, and the skill teaches your agent to use it. Install the sling CLI.
WarpBuildNo. WarpBuild has no CLI of its own; its Docker builders work from the Docker CLI.
Agent skills that optimize your CI
StarSlingYes. ci-speedup for wall clock, ci-score for configuration and ci-secure for security: each reads your workflows and hands your coding agent the evidence to fix them. Works with your existing runner provider.
WarpBuildWarpBuild runs an MCP server for creating runners and images through its API, and has no agent skills.
Speed vs GitHub-hosted runners
StarSlingYes. Up to 2.32x faster than GitHub-hosted runners with Adaptive Compute. Adaptive Compute: up to 2.32x faster than GitHub-hosted runners. StarSling tops the GitHub Actions runner benchmarks.
WarpBuildYes:Faster than GitHub-hosted runners.
Unlimited concurrency
StarSlingYes. Concurrency is unlimited.
WarpBuildYes. Unlimited concurrency on WarpBuild's Linux and Windows runners.
Drop-in runner replacement
StarSlingYes, swap ubuntu-latest for starsling-ubuntu-26.04.
WarpBuildYes, a drop-in GitHub Actions runner replacement via the runs-on label.
GitHub Actions support
StarSlingYes. Runs existing GitHub Actions workflows.
WarpBuildYes. Runs existing GitHub Actions workflows.
Docker builds
StarSlingNo separate builder service: Docker builds run inside your workflow on StarSling runners, and the agents propose build and cache fixes as reviewable PRs.
WarpBuildRemote "Docker builders" with Buildx integration, each builder profile keeping a persistent layer cache across builds, with amd64 and arm64 multi-arch builds and per-session billing.
Caching
StarSlingGitHub Actions caching works unchanged; the agents open PRs that fix cache keys, cache misses, and unnecessary installs.
WarpBuildShips WarpBuilds/cache@v1, compatible with actions/cache@v4 and usable as a drop-in replacement, plus cache-aware setup actions; hosted cache storage is billed per GB-month and is not supported on Windows runners.
Runner OS coverage
StarSlingUbuntu 26.04 or 24.04 Linux runners.
WarpBuildLinux x64 and ARM64, macOS, and Windows runner families.
Primary focus
StarSlingFast runners plus agent-native optimization of the pipeline.
WarpBuildFast drop-in runners plus a container-build service (remote Docker builders and a hosted Actions cache).
Pricing model
StarSlingUsage-based per-minute, from $0.004/min (2 vCPU) to $0.128/min (64 vCPU); queue time never billed; no seat fees.
WarpBuildUsage-based per-minute billing, priced by runner size, with Docker builders billed per builder session and cache storage billed per GB-month.
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Faster

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 tops the GitHub Actions runner benchmarks

Savings

Day one
From moving the same unchanged suite onto our runners.
Over time
After the optimization agents have worked on the suite.
Pricing

Agent-native CI

Agent-native means three things: skills your coding agent runs, a CLI it reads CI through, and agents that open the PRs.

Why choose StarSling over WarpBuild?

Choose StarSling to improve the whole GitHub Actions workflow: compute, caching, installs, parallelization, and test execution, with changes delivered as reviewable PRs.

  • Give each job faster compute: Adaptive Compute combines Sandbox Router's placement on the fastest available sandbox with Afterburner's extra CPU and RAM during a running step, at no extra cost.
  • Improve the work your pipeline performs: StarSling agents deliver reviewable optimization PRs for workflow improvements. Inspect the changes in real repositories and merge the ones that fit your team.
  • Turn CI findings into fixes: ci-speedup, ci-score, and ci-secure give your coding agent workflow-specific findings and fixes for speed, configuration, and security, applying CI optimization best practices.
  • Own your code review: Review Runners run your chosen model, repo-native skills, scripts, and team-defined reviewers. Version review logic alongside your code.
  • Give GPU tests their own hardware: GPU Runners provide dedicated NVIDIA GPUs for GPU tests, CUDA builds, and model evaluations, keeping CI off your production GPUs.
  • Diagnose failures and wasted time: the sling CLI explains failed jobs with evidence and next steps and breaks wall-clock time into runner-lifecycle phases.

Benchmarks: StarSling vs WarpBuild

In RunsOn's public GitHub Actions runner benchmark of Rust and TypeScript builds on x64 runners at 8 to 12 vCPU (p90 wait + job time, September 30 to October 4, 2026), StarSling ranked first on both builds with Rust 1m 54s and TypeScript 1m 07s. WarpBuild recorded Rust 2m 14s and TypeScript 1m 34s.

Each figure is a provider's best runner in that size range, on a cold Rust build and a cold TypeScript build. RunsOn runs the benchmark and sells one of the runners it measures. Its harness and raw results carry all nine providers, and our write-up walks through them.

Real StarSling results on existing GitHub Actions workflows

WarpBuild centers on fast runners, remote Docker builders, and a hosted cache. StarSling's customer results come from keeping teams on GitHub Actions and letting agents improve the workflow itself. Each case study carries its measurement window and source method.

  • Better Auth: StarSling agents fixed CI cache and install waste; E2E went from 2m 22s to 1m 04s and CI went from 1m 40s to 1m 02s.
  • Mastra: agents opened nineteen PRs, including sharding, healthchecks, polling, and runner migration; Combined store Tests measured 29m 56s to 5m 06s in the post-migration window.
  • Partcl: the agents shipped eight optimization PRs on a synthesis-bound workload, cutting heaviest-job compute cost 13x per run and p95 queue time from 9.5 minutes to 35 seconds.

Best fit

Choose StarSling if

Teams that want Adaptive Compute for faster jobs, agent PRs and skills that improve CI, configurable code review agents, and dedicated GPUs for tests and model evaluations.

Choose WarpBuild if

Teams whose bottleneck is container image builds, who want a managed remote Docker builder with a persistent layer cache and multi-arch output, or who need macOS and Windows runner families alongside Linux.

FAQ

Why choose StarSling over WarpBuild?

Choose StarSling to improve the whole GitHub Actions workflow: compute, caching, installs, parallelization, and test execution, with changes delivered as reviewable PRs. Adaptive Compute improves job placement and supplies extra CPU and RAM during running steps. Agents deliver workflow optimization PRs, and CI skills identify and help fix speed, configuration, and security issues. Review Runners let you define your reviewers, while GPU Runners provide dedicated hardware for GPU tests and model evaluations.

How is StarSling different from WarpBuild?

Both are fast, drop-in GitHub Actions runners. WarpBuild sells build infrastructure around the runner: remote Docker builders with a persistent layer cache, and a WarpBuilds/cache drop-in for actions/cache. StarSling sells the layer above the runner: AI agents that read your workflows, logs, and telemetry and open optimization PRs for caching, installs, parallelization, and test sharding, so the pipeline itself keeps getting faster.

Does StarSling have a WarpBuild-style remote Docker builder or cache action?

No. StarSling does not ship a separate remote-builder service or a replacement cache action. Your Docker builds and your actions/cache steps keep running inside your workflow, on faster hardware, and StarSling's agents open PRs that fix the build and cache steps you already have.

Is StarSling a drop-in replacement like WarpBuild?

Yes. Swap your runs-on label to starsling-ubuntu-26.04; your existing workflows stay the same.

Other comparisons

Compare StarSling with the other runner and CI options teams evaluate.

References

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