AI Tools · head to head
Lambda Labs vs CoreWeave
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; CoreWeave gPU nodes are sold as full 8 GPU instances rather than single cards, so the entry cost for an H100 node is $49.24 an hour on demand
- They diverge on capability: Lambda Labs covers NVIDIA GPUs, CoreWeave covers NVIDIA H100/A100.
Where they differ
Only the attributes on which Lambda Labs and CoreWeave actually diverge.
| Attribute | Lambda Labs | CoreWeave |
|---|---|---|
| Starting price | $1.1/per-hour | $0.35/per-hour |
| Founded | 2012 | 2017 |
Identical on both: pricing model (usage-based), free tier (No), platforms (Cloud), 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
- Persistent storage
- SSH access
- JupyterLab
- VSCode
- SSH
Only in CoreWeave
- NVIDIA H100/A100
- Kubernetes native
- High bandwidth
- Object storage
- Kubernetes
- Terraform
- Cloud APIs
Both cover
- 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 CoreWeave
- Short term access to high memory accelerators without buying hardwarenot CoreWeave
CoreWeave
- Renting GPU compute for model training and inferencenot Lambda Labs
- Running large scale AI workloads without buying hardwarenot 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
CoreWeave
- GPU nodes are sold as full 8 GPU instances rather than single cards, so the entry cost for an H100 node is $49.24 an hour on demand
- Spot pricing is roughly 40% of on demand, at $19.71 an hour for the same H100 node, so predictable capacity carries a large premium
- The newest hardware carries no published price and requires contacting sales
- Discounts of up to 60% require committed usage agreements negotiated with sales
- Only the GH200 is offered as a single GPU instance
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
CoreWeave
$0.35/per-hour- Standard$0.35/per-hour
- Various GPU types
- Kubernetes
- EnterpriseFree
- Dedicated clusters
- Custom solutions
Which should you pick?
Choose Lambda Labs if
- You need nvidia gpus.
- You work on Cloud.
- You also want pre-installed frameworks.
Choose CoreWeave if
- You need nvidia h100/a100.
- You work on Cloud.
- You also want kubernetes native.
Questions people ask
- Is Lambda Labs or CoreWeave better?
- Neither clearly leads. Lambda Labs starts at $1.1/per-hour and CoreWeave at $0.35/per-hour, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Lambda Labs or CoreWeave?
- Lambda Labs starts at $1.1/per-hour and CoreWeave at $0.35/per-hour.
- Does Lambda Labs or CoreWeave run on more platforms?
- Both run on Cloud, so platform support will not decide this one for you.
- 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 CoreWeave is typically brought in for.
- What can Lambda Labs do that CoreWeave cannot?
- Lambda Labs covers NVIDIA GPUs, Pre-installed frameworks, Persistent storage, SSH access. CoreWeave covers NVIDIA H100/A100, Kubernetes native, High bandwidth, Object storage. Both handle Cloud support.