AI Tools · head to head
Banana vs Lambda Labs
The short version
- Each has a real cost: Banana banana shut down its serverless GPU infrastructure on 31 March 2024 at noon PST and told customers to migrate to another provider by that time; Lambda Labs on demand capacity is first come access rather than guaranteed, so an instance type can be unavailable when needed
- They diverge on capability: Banana covers GPU inference, Lambda Labs covers NVIDIA GPUs.
Where they differ
Only the attributes on which Banana and Lambda Labs actually diverge.
| Attribute | Banana | Lambda Labs |
|---|---|---|
| Starting price | $0.0005/per-second | $1.1/per-hour |
| Platforms | Cloud, Api | Cloud |
| Founded | 2021 | 2012 |
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 Banana
- GPU inference
- Auto-scaling
- Docker deployment
- Low latency
- REST API
- Python SDK
- Api support
Only in Lambda Labs
- NVIDIA GPUs
- Pre-installed frameworks
- Persistent storage
- SSH access
- JupyterLab
- VSCode
- SSH
Both cover
- Cloud support
What people use each for
The jobs each tool is most often brought in to do.
Banana
- Historically, serverless GPU inference for machine learning modelsnot Lambda Labs
- Migration reference for teams that ran models on Banana before the 2024 shutdownnot Lambda Labs
Lambda Labs
- Renting GPU instances for model training and inferencenot Banana
- Short term access to high memory accelerators without buying hardwarenot Banana
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Banana
- Banana shut down its serverless GPU infrastructure on 31 March 2024 at noon PST and told customers to migrate to another provider by that time
- The vendor's own sunset notice names limited runway, retention problems and GPU supply constraints as the reasons for closing
- The banana.dev site still displays pricing tiers, but every tier links to the sunset notice rather than to a purchase
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
Pricing, plan by plan
Banana
$0.0005/per-second- Starter$0.0005/per-second
- A10G GPU
- Basic support
- ScaleFree
- Volume discounts
- Dedicated support
Lambda Labs
$1.1/per-hour- On-Demand$1.1/per-hour
- A10 GPU
- Instant availability
- ReservedFree
- Volume discounts
- Guaranteed capacity
Which should you pick?
Choose Banana if
- You need gpu inference.
- You work on Cloud, Api.
- You also want auto-scaling.
Choose Lambda Labs if
- You need nvidia gpus.
- You work on Cloud.
- You also want pre-installed frameworks.
Questions people ask
- Is Banana or Lambda Labs better?
- Neither clearly leads. Banana starts at $0.0005/per-second and Lambda Labs at $1.1/per-hour, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Banana or Lambda Labs?
- Banana starts at $0.0005/per-second and Lambda Labs at $1.1/per-hour.
- Does Banana or Lambda Labs run on more platforms?
- Banana runs on Cloud, Api. Lambda Labs runs on Cloud.
- What is Banana best used for?
- Banana is most often used for historically, serverless gpu inference for machine learning models, migration reference for teams that ran models on banana before the 2024 shutdown. Of those, historically, serverless gpu inference for machine learning models and migration reference for teams that ran models on banana before the 2024 shutdown are not what Lambda Labs is typically brought in for.
- What can Banana do that Lambda Labs cannot?
- Banana covers GPU inference, Auto-scaling, Docker deployment, Low latency. Lambda Labs covers NVIDIA GPUs, Pre-installed frameworks, Persistent storage, SSH access. Both handle Cloud support.