GitHub Actions runners benchmark

This page offers a detailed comparison of CPU speeds, queuing times, and disk performance for various providers of GitHub Actions self-hosted runners. The aim is to assist in identifying the best GitHub Actions self-hosted runner provider for your projects, based on your specific needs.

An analysis is provided below the benchmark results. Note that this benchmark is published by RunsOn, so you might consider me biased, but I try my best to provide a fair comparison with the details available.

Providers included in the benchmark

Official:

GitHub (Azure)

Self-hosted alternatives:

👋 RunsOn (AWS)
AWS CodeBuild (AWS)

Third-party alternatives:

Buildjet (Hetzner)
Blacksmith (Hetzner / Secured Servers LLC)
Namespace (Hetzner)
Ubicloud (Hetzner)
Cirrus (Hetzner)

Note: Warpbuild and Depot are third-party providers that resell AWS instances, but they forbid benchmarking their platform 🤷.

CPU speed and queuing times

Last updated: Dec 4, 2024

Benchmarks are performed using the Passmark benchmarking tool ↗, using the CPU Single Threaded metric. The table displays the last 60 days of data, before the last updated date.

Key metrics such as the processor model, single-thread CPU speed, queue time, pricing, and the underlying infrastructure provider are compared. The CPU single-threaded rating is a crucial metric as it is the most significant factor (unless your job is massively parallel) in accelerating any of your workflows.

x64 runners

Provider	CPU speed (p50 \| p95)	Queue time (s) (p50 \| p95)	Processor	Infra	Samples
Blacksmith (2x cheaper) blacksmith-2vcpu-ubuntu-2204	3898 \| 4168	22 \| 24	AMD EPYC (x86_64)	Hetzner Online	21
Namespace (2x cheaper) nscloud-ubuntu-22.04-amd64-2x8	3912 \| 4019	20 \| 23	AMD EPYC (x86_64)	Hetzner Online	23
Buildjet (2x cheaper) buildjet-2vcpu-ubuntu-2204	3267 \| 3475	24 \| 38	AMD Ryzen 9 5950X 16-Core Processor (x86_64)	Hetzner Online	12
Cirrus (fixed price per runner) ghcr.io/cirruslabs/ubuntu-runner-amd64:22.04-md	3224 \| 3230	26 \| 31	Intel Xeon Gold 5412U (x86_64)	Hetzner Online GmbH	23
RunsOn (10x cheaper) runs-on,family=r7iz	3082 \| 3135	27 \| 61	Intel Xeon Gold 6455B (x86_64)	Amazon.com	23
RunsOn (10x cheaper) runs-on,family=c7a	2883 \| 2884	29 \| 44	AMD EPYC 9R14 (x86_64)	Amazon.com	23
RunsOn (10x cheaper) runs-on,family=m7i-flex	2755 \| 2949	30 \| 44	Intel Xeon Platinum 8488C (x86_64)	Amazon.com	23
Ubicloud (10x cheaper) ubicloud-standard-2	2576 \| 2591	17 \| 39	AMD EPYC 9454P 48-Core Processor (x86_64)	Hetzner Online	23
GitHub github-16cpu-x64	2397 \| 2401	8 \| 98	AMD EPYC 7763 64-Core Processor (x86_64) (custom)	Microsoft Azure	23
GitHub ubuntu-22.04 ubuntu-latest	2291 \| 2298	10 \| 12	AMD EPYC 7763 64-Core Processor (x86_64)	Microsoft Azure	21
AWS CodeBuild codebuild-ubuntu-7.0-small codebuild-ubuntu-7.0-large codebuild-ubuntu-7.0-medium	2090 \| 2151	45 \| 75	Intel Xeon Platinum 8275CL CPU @ 3.00GHz (x86_64)	Amazon.com	47
AWS CodeBuild codebuild-ubuntu-7.0-medium codebuild-ubuntu-7.0-large codebuild-ubuntu-7.0-small	2009 \| 2032	46 \| 108	Intel Xeon Platinum 8124M CPU @ 3.00GHz (x86_64)	Amazon.com	19
Warpbuild (2x cheaper) N/A	N/A	N/A	N/A	Amazon.com	0
Depot (2x cheaper) N/A	N/A	N/A	N/A	Amazon.com	0

arm64 runners

Provider	CPU speed (p50 \| p95)	Queue time (s) (p50 \| p95)	Processor	Infra	Samples
RunsOn (10x cheaper) runs-on,family=r8g	1934 \| 1935	27 \| 31	Neoverse-V2 (aarch64)	Amazon.com	20
RunsOn (10x cheaper) runs-on,family=m7g	1543 \| 1549	29 \| 31	(aarch64)	Amazon.com	20
Cirrus (fixed price per runner) ghcr.io/cirruslabs/ubuntu-runner-arm64:22.04-md	1325 \| 1326	24 \| 33	Neoverse-N1 (aarch64)	Hetzner Online GmbH	20
GitHub github-2cpu-arm64	1321 \| 1323	9 \| 93	Neoverse-N1 (aarch64)	Microsoft Azure	20
Blacksmith (2x cheaper) blacksmith-2vcpu-ubuntu-2204-arm	1318 \| 1321	24 \| 32	Neoverse-N1 (aarch64)	Hetzner Online	20
Ubicloud (10x cheaper) ubicloud-standard-2-arm	1317 \| 1322	17 \| 18	Neoverse-N1 (aarch64)	Hetzner Online	20
Namespace (2x cheaper) nscloud-ubuntu-22.04-arm64-2x8	1305 \| 1315	25 \| 26	Neoverse-N1 (aarch64)	Hetzner Online	20
Buildjet (2x cheaper) buildjet-2vcpu-ubuntu-2204-arm	1323 \| 1324	39 \| 59	Neoverse-N1 (aarch64)	Hetzner Online	19
Warpbuild (2x cheaper) N/A	N/A	N/A	N/A	Amazon.com	0
Depot (2x cheaper) N/A	N/A	N/A	N/A	Amazon.com	0

Observations

Namespace and Buildjet have the best single-threaded performance for x64 (gaming CPUs instead of server CPUs). Would be great if AWS was able to offer similar performance for x64. Note that Buildjet doesn’t ensure the same CPU model for an identical runner type, so you might get a slower runner at random (not great for reproducibility).
RunsOn has the best performance for arm64. Hetzner-based providers don’t have access to the latest ARM CPUs (yet).
GitHub uses outdated and slow CPUs for x64. arm64 is better, but not widely available yet. Queue times are very good, although larger runners are reported to wildly vary in terms of queuing time (sometimes multiple minutes).
Cheapest providers are RunsOn and Ubicloud.
Default AWS CodeBuild instances are even slower than GitHub, and pricing is not competitive. Queueing time is also high.

Missing from the benchmark:

Testing concurrency and scaling limits of each provider. Hetzner is not yet at the scale of AWS, and bumping concurrency limits at Hetzner-based providers is a manual request, and sometimes costly (e.g. buildjet). Companies with many thousands of jobs per day might prefer the scalability of AWS.

Disk performance

While CPU speed is the most important factor for most workflows, disk performance can be the limiting factor in specific scenarios that require a high number of IOPS. That’s why it is important to be able to pick runner types that match your needs.

The table below compares the disk performance of various providers. Sequential read and write performance is compared, as well as random read and write performance. Sequential performance is more important when dealing with large files, while random performance is more important for small, many files. Benchmark is run as per this Google Cloud article ↗ and measures the performance on the disk where the GITHUB_WORKSPACE resides. I performed 3 runs and picked the best result for each provider, although I didn’t notice much variance across runs.

For RunsOn, multiple instance types are compared, to highlight the performance difference between:

instance types with locally attached NVMe volumes vs EBS-only instances. When an instance has local storage in addition to EBS, the results are for the local storage only (EBS results stay the same).
storage bandwidth scaling of locally attached NVMe volumes with instance size, since on AWS larger instances are allocated a higher percentage of the storage bandwidth ↗ of the underlying host.

Note that RunsOn automatically mounts and formats the local instance storage volumes for you. If multiple volumes are available, they are automatically mounted in a RAID-0 configuration, to maximize disk space and performance.

The default sorting of the table is by Random writes, because this is where the network-attached EBS volumes show their main limitation. You can click on the column header to sort by a different metric.

Results

Provider	Type	Configuration	Seq Writes (MiB/s)	Rand Writes (MiB/s)	Seq Reads (MiB/s)	Rand Reads (MiB/s)	Infrastructure
RunsOn	c6id.24xlarge	5312 GiB (4 * 1328 GiB NVMe SSD)	3435	1495	7332	1564	AWS
RunsOn	c5ad.24xlarge	3540 GiB (2 * 1770 GiB NVMe SSD)	2966	1465	6353	1285	AWS
RunsOn	c7gd.12xlarge	2656 GiB (2 * 1328 GiB NVMe SSD)	1699	1402	3664	1648	AWS
RunsOn	c5ad.12xlarge	1676 GiB (2 * 838 GiB NVMe SSD)	1479	1315	3177	1313	AWS
RunsOn	c7gd.metal (equivalent to c7gd.16xlarge)	3540 GiB (2 * 1770 GiB NVMe SSD)	2285	1286	4899	1483	AWS
Cirrus	ghcr.io/cirruslabs/ubuntu-runner-arm64:22.04-md	47 GiB SSD	2680	1162	34500	1140	Hetzner
RunsOn	c7gd.8xlarge	1770 GiB NVMe SSD	1135	1038	2448	1688	AWS
Namespace	nscloud-ubuntu-22.04-arm64-2x8	98 GiB SSD	2501	638	4960	831	Hetzner
RunsOn	c7gd.4xlarge	884 GiB NVMe SSD	574	508	1205	1051	AWS
Ubicloud	ubicloud-standard-2-arm	86 GiB SSD	1079	316	1149	443	Hetzner
RunsOn	c5ad.4xlarge	560 GiB (2 * 280 GiB NVMe SSD)	242	219	604	511	AWS
Buildjet	buildjet-2vcpu-ubuntu-2204-arm	118 GiB SSD	1819	165	8746	320	Hetzner
RunsOn	c6id.xlarge	220 GiB NVMe SSD	146	131	303	262	AWS
RunsOn	c7gd.xlarge	220 GiB NVMe SSD	147	131	303	262	AWS
Blacksmith	blacksmith-2vcpu-ubuntu-2204-arm	130 GiB SSD	143	93	44	1271	Hetzner
RunsOn	c7gd.large	110 GiB NVMe SSD	75	66	153	131	AWS
RunsOn	c7gd.medium	55 GiB NVMe SSD	41	33	80	66	AWS
GitHub	2cpu-arm64	75 GiB, Network volume	199	17	203	28	Azure
RunsOn	c7g.medium	40 GiB, EBS only, 400MiB provisioned throughput	404	16	406	16	AWS
RunsOn	c7g.medium	80 GiB, EBS only, 750MiB provisioned throughput	730	16	755	16	AWS

Observations

Network-attached volumes

Sequential read/write of network-attached volumes is actually pretty good, and you get what you pay for in terms of volume throughput provisioning. Interestingly it can be higher than some providers with local SSDs (gp3 volumes can provision up to 1000MiB/s of throughput).
At the same time, random read/write performance of network-attached volumes is… not great, reaching only up to 20MiB/s. This is the case for default runner types at GitHub, RunsOn, and other providers at AWS.

The good news is that poor random read/write performance has a surprisingly low impact in the context of most CI workflows, where the sequential performance is often more relevant, as you’ll be pulling / writing large cache files, tarballs, artefacts, or docker images from the network, and then executing mostly CPU-intensive tasks.

However some workflows will require very large amounts of space and/or much improved random performance, and that’s where it’s important to be able to also pick a runner with local SSDs when you need it.

Local SSDs

If you want the fastest sequential AND random write performance, AWS with locally-attached NVMe volumes is your friend. Although you will need to choose larger instance types due to the linear scaling of the storage bandwidth with the instance size. You also get access to terabytes of local storage if you need it.
Performance of AWS locally-attached NVMe volumes is identical whether you select an x64 or arm64 instance.
Cirrus has really high sequential read performance, and good performance overall. Namespace as well. I suppose (reach out if I’m wrong!) that contrary to AWS they are not throttling bandwidth so performance could suffer from noisy neighbours on the same host. Probably same story with Buildjet and Ubicloud, which have lower performance as well. Blacksmith is probably suffering from this issue, since the disk performance is much lower than the other providers at Hetzner (except for random reads, for some reason).
Among Hetzner providers, max disk space is currently limited to 130GiB (Blacksmith). AWS allows up to 64 TiB for EBS volumes, and offers instance types that can go up to 305 TiB GB of local storage.

RunsOn allows to select instances with local SSDs (of variable sizes and performance), and automatically mount them.

Make your choice!

Note: this analysis is valid as of 2024/11/04. Things change quickly in this space, so make sure you do your own research as well.

Best alternatives for self-hosted GitHub Actions runners

The best alternatives for self-hosted GitHub Actions runners will heavily depend on your primary requirement:

Cheapest pricing: RunsOn or Ubicloud. Cirrus can also be a good option, if the fixed price/runner pricing model makes sense for you.
Fastest machines: Buildjet, Namespace, Cirrus have the fastest CPUs for x64 jobs. Be aware that they are hosted at Hetzner, with variable performance for the network speeds. RunsOn has the fastest performance for arm64, and good performance for x64.
GPU support: RunsOn is the only alternative provider that currently offers GPU support. GitHub restricts custom GPU runners to higher-tier plans, and they are expensive.
Windows support: RunsOn is the only alternative provider that currently offers Windows support.
Low queue times: GitHub has the best queue time for standard runners, and all alternatives are ~ok on that front.
Self-hosted deployment: RunsOn is the only solution that is entirely hosted in your AWS infrastructure, with no third-party or centralized service. You can also choose the actions-runner-controller ↗ (ARC) project to self-host in Kubernetes, although it is more complex and expensive to setup, maintain, and operate.
macOS support: many third-party providers offer macOS runners. On AWS, Apple is currently forcing a 24h reservation for macOS hosts, which is not ideal for short-lived CI jobs. As such, this can only work when a centralized service is pooling jobs for many clients, which is not the case e.g. for RunsOn.

When should I use GitHub’s official actions runners?

GitHub’s official actions runners are best used for short-lived jobs or those that do not require fast CPUs. They boot quickly, making them ideal for smaller, less intensive tasks. However, for larger or more CPU-intensive jobs, consider alternative runners due to the slower performance and higher costs of GitHub’s larger runners. Be aware that GitHub bills by the minute, even if your job only runs for a few seconds.