AI Tools · head to head
Lambda Labs vs RunPod
The short version
- Each has a real cost: Lambda Labs on demand capacity is first come access rather than guaranteed, so an instance type can be unavailable when needed; RunPod idle volume disk storage is billed at $0.20 per GB per month, double the $0.10 per GB per month charged while the pod is running
- They diverge on capability: Lambda Labs covers NVIDIA GPUs, RunPod covers GPU instances.
Where they differ
Only the attributes on which Lambda Labs and RunPod actually diverge.
| Attribute | Lambda Labs | RunPod |
|---|---|---|
| Starting price | $1.1/per-hour | $0.2/per-hour |
| Platforms | Cloud | Cloud, Api |
| Founded | 2012 | 2022 |
Identical on both: pricing model (usage-based), free tier (No), user rating (Not yet rated), category (AI Tools).
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 Lambda Labs
- NVIDIA GPUs
- Pre-installed frameworks
- JupyterLab
- VSCode
- SSH
Only in RunPod
- GPU instances
- Serverless
- Templates
- Docker
- REST API
- Api support
Both cover
- Persistent storage
- SSH access
- Cloud support
What people use each for
The jobs each tool is most often brought in to do.
Lambda Labs
- Renting GPU instances for model training and inferencenot RunPod
- Short term access to high memory accelerators without buying hardwarenot RunPod
RunPod
- Renting GPU compute by the second for model training and inferencenot Lambda Labs
- Running serverless GPU workers that scale with request volumenot Lambda Labs
- Attaching persistent network storage shared across GPU podsnot Lambda Labs
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Lambda Labs
- On demand capacity is first come access rather than guaranteed, so an instance type can be unavailable when needed
- H100 pricing varies within a band, at $3.99 to $4.29 an hour per GPU, so the rate is not fixed
- Reserved capacity is arranged by contacting the team rather than self serve
- Prices are quoted before applicable tax
RunPod
- Idle volume disk storage is billed at $0.20 per GB per month, double the $0.10 per GB per month charged while the pod is running
- Reserved clusters of all terms from 1 to 12 months are priced by contacting sales with no published rate
- L40S, H100 SXM and B200 cluster configurations are listed as contact sales rather than at a published hourly rate
- High performance network storage costs $0.14 per GB per month, twice the standard sub 1TB rate of $0.07
Pricing, plan by plan
Lambda Labs
$1.1/per-hour- On-Demand$1.1/per-hour
- A10 GPU
- Instant availability
- ReservedFree
- Volume discounts
- Guaranteed capacity
RunPod
$0.2/per-hour- Community Cloud$0.2/per-hour
- Affordable GPUs
- Spot instances
- Secure Cloud$0.44/per-hour
- Enterprise security
- Dedicated hardware
Which should you pick?
Choose Lambda Labs if
- You need nvidia gpus.
- You work on Cloud.
- You also want pre-installed frameworks.
Choose RunPod if
- You need gpu instances.
- You work on Cloud, Api.
- You also want serverless.
Questions people ask
- Is Lambda Labs or RunPod better?
- Neither clearly leads. Lambda Labs starts at $1.1/per-hour and RunPod at $0.2/per-hour, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Lambda Labs or RunPod?
- Lambda Labs starts at $1.1/per-hour and RunPod at $0.2/per-hour.
- Does Lambda Labs or RunPod run on more platforms?
- Lambda Labs runs on Cloud. RunPod runs on Cloud, Api.
- What is Lambda Labs best used for?
- Lambda Labs is most often used for renting gpu instances for model training and inference, short term access to high memory accelerators without buying hardware. Of those, renting gpu instances for model training and inference and short term access to high memory accelerators without buying hardware are not what RunPod is typically brought in for.
- What can Lambda Labs do that RunPod cannot?
- Lambda Labs covers NVIDIA GPUs, Pre-installed frameworks, JupyterLab, VSCode. RunPod covers GPU instances, Serverless, Templates, Docker. Both handle Persistent storage, SSH access, Cloud support.