Softwr

Developer Tools · head to head

Dagger vs Lambda

Dagger logo

Dagger

Developer Tools

Programmable CI/CD engine that runs your pipeline as containers on any runner

From
Free
Free plan
Yes
Full reviewWebsite
Lambda logo

Lambda

Cloud

GPU supercomputers for AI training and inference at enterprise scale

From
On request
Free plan
No
Full reviewWebsite

The short version

  • Only Dagger has a free tier, so it costs nothing to try first.
  • Each has a real cost: Dagger dagger is not a CI provider, so you keep paying for GitHub Actions or GitLab runners underneath it; the Dagger Cloud subscription is an addition to your CI bill, not a replacement for it.; Lambda no free tier or trial, requiring immediate commitment for testing
  • They diverge on capability: Dagger covers Pipelines as code, Lambda covers Superclusters.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Dagger and Lambda actually diverge.

Attributes where Dagger and Lambda differ
AttributeDaggerLambda
Starting priceFreeOn request
Pricing modelPer month per team for Dagger CloudPay-as-you-go hourly pricing with volume discounts for reserved capacity
Free tierYesNo
PlatformsLinux, macOS, Windows, Self-hostedCloud
CategoryDeveloper ToolsCloud
FoundedUnknown2012

Identical on both: user rating (Not yet rated).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Dagger

  • Pipelines as code
  • Local and CI parity
  • Content-addressed caching
  • Dagger Functions and modules
  • CI-provider agnostic
  • Dagger Cloud traces
  • GitHub Checks integration
  • Container-native execution

Only in Lambda

  • Superclusters
  • 1-Click Clusters
  • On-demand instances
  • Liquid cooling
  • InfiniBand networking
  • Managed orchestration
  • Co-engineering support

What people use each for

The jobs each tool is most often brought in to do.

Dagger

  • A platform team maintaining near-identical build YAML across forty repositories that wants one versioned module every repository calls insteadnot Lambda
  • An engineering organisation migrating off a CI provider that does not want to rewrite every pipeline as part of the migrationnot Lambda
  • A team whose engineers waste hours pushing commits to debug CI-only failures and needs to reproduce the exact run locallynot Lambda
  • A monorepo where most commits touch a small subset of services and cache-accurate step skipping cuts build minutes materiallynot Lambda

Lambda

  • Training foundation models at scale with dedicated GPU infrastructurenot Dagger
  • Large-scale inference serving on enterprise-grade hardwarenot Dagger
  • Multi-GPU distributed training with InfiniBand networkingnot Dagger
  • Single-tenant secure compute for regulated industriesnot Dagger
  • AI lab infrastructure for frontier model developmentnot Dagger

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Dagger

  • Dagger is not a CI provider, so you keep paying for GitHub Actions or GitLab runners underneath it; the Dagger Cloud subscription is an addition to your CI bill, not a replacement for it.
  • Writing pipelines in Go or TypeScript raises the barrier to entry: a release engineer who could edit a YAML step now needs to read code, and the people who can fix a broken build shrink to those comfortable with the SDK.
  • The engine runs as a container on the runner and needs a persistent cache volume to deliver its main benefit, so ephemeral CI runners give you correctness without the speed, and provisioning durable cache storage is extra platform work.
  • The Team plan caps at ten users and ten million events per month; an organisation of any size crosses that quickly and moves to Enterprise pricing that is not published, so cost at scale is unknowable up front.
  • The module ecosystem is young and thinly maintained relative to the marketplace of a mature CI provider, so integrations that exist as a one-line Action often have to be written yourself as a Dagger function.

Lambda

  • No free tier or trial, requiring immediate commitment for testing
  • Single-tenant Superclusters require custom pricing discussions
  • Pricing complexity across multiple GPU types and cluster sizes
  • Less suitable for experimentation or small teams with tight budgets

Pricing, plan by plan

Dagger

Free
  • IndividualFree
    • One user
    • One million events per month
    • Workflow logs and function call traces
  • Team$50/month
    • Up to ten users
    • Ten million events per month
    • Module insights and module catalogue
  • Enterprise$undefined/year
    • Custom user and event limits
    • SSO
    • Managed single-tenant deployment

Lambda

On request
  • 1-Click Clusters B200$undefined/hourly
    • 16 GPUs: $9.86/GPU/hour
    • 256+ GPUs: $8.87/GPU/hour
    • 1-year+ reserved discounts available
  • 1-Click Clusters H100$undefined/hourly
    • 16 GPUs: $6.16/GPU/hour
    • 256+ GPUs: $5.54/GPU/hour
  • On-Demand Instances B200$undefined/hourly
    • SXM6: $6.69/GPU/hour
  • On-Demand Instances H100$undefined/hourly
    • SXM: $3.99/GPU/hour

Which should you pick?

Choose Dagger if

  • You need pipelines as code.
  • You want to start without paying.
  • You work on Linux, macOS, Windows, Self-hosted.
  • You also want local and ci parity.
Dagger review

Choose Lambda if

  • You need superclusters.
  • You work on Cloud.
  • You also want 1-click clusters.
Lambda review

Questions people ask

Is Dagger or Lambda better?
Neither clearly leads. Dagger starts at Free and Lambda at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Dagger or Lambda?
Dagger has a free tier; the other does not. Paid plans start at Free for Dagger and On request for Lambda.
Does Dagger or Lambda run on more platforms?
Dagger runs on Linux, macOS, Windows, Self-hosted. Lambda runs on Cloud.
Can I use Dagger for free?
Yes. Dagger has a free tier, so you can try it without paying. Lambda starts at On request.
What is Dagger best used for?
Dagger is most often used for a platform team maintaining near-identical build yaml across forty repositories that wants one versioned module every repository calls instead, an engineering organisation migrating off a ci provider that does not want to rewrite every pipeline as part of the migration, a team whose engineers waste hours pushing commits to debug ci-only failures and needs to reproduce the exact run locally, a monorepo where most commits touch a small subset of services and cache-accurate step skipping cuts build minutes materially. Of those, a platform team maintaining near-identical build yaml across forty repositories that wants one versioned module every repository calls instead and an engineering organisation migrating off a ci provider that does not want to rewrite every pipeline as part of the migration are not what Lambda is typically brought in for.
What can Dagger do that Lambda cannot?
Dagger covers Pipelines as code, Local and CI parity, Content-addressed caching, Dagger Functions and modules. Lambda covers Superclusters, 1-Click Clusters, On-demand instances, Liquid cooling.

Answered from the vendors’ own pages

Dagger: Does Dagger replace GitHub Actions?

No. Dagger runs inside GitHub Actions or any other CI. It replaces the YAML that describes your pipeline steps, not the trigger and runner layer.

Lambda: What makes Lambda's infrastructure different?

Lambda offers single-tenant Superclusters with exclusive GPU access, liquid cooling, and NVIDIA Quantum-2 InfiniBand networking. The company is 100% focused on AI infrastructure with co-engineering support from teams who built infrastructure for major AI labs.

Source
Dagger: Is the engine open source?

Yes, the Dagger engine and SDKs are open source and free. Dagger Cloud, the observability product, is what costs money.

Lambda: How does pricing work for large clusters?

1-Click Clusters pricing ranges from $5.54-$9.86 per GPU/hour depending on GPU type and cluster size, with volume discounts for 256+ GPUs. Reserved capacity is available at custom pricing for 1-year+ commitments.

Source
Dagger: What is an event in the pricing?

Dagger Cloud meters pipeline telemetry events. One million per month is free; the Team plan at 50 USD per month allows ten million.

Lambda: Which GPU types are available?

Lambda offers NVIDIA B200, H100, A100, and Tesla V100 GPUs. Individual instances range from V100 at $0.79/hour to B200 SXM6 at $6.69/hour. Newer models like Vera Rubin are available in Superclusters.

Source
Dagger: Can I run the same pipeline on my laptop?

Yes, that is the main reason teams adopt it. The dagger CLI executes the identical graph locally, so CI-only failures become reproducible.

Share

Related pages

More on Dagger

More on Lambda

Keep looking

Other head to heads