Cloud · head to head
Lambda vs Wasabi

Lambda
Cloud
GPU supercomputers for AI training and inference at enterprise scale
- From
- On request
- Rated
- -
The short version
- Each has a real cost: Lambda no free tier or trial, requiring immediate commitment for testing; Wasabi 90-day minimum storage duration with no option to delete before full period without penalty
- They diverge on capability: Lambda covers Superclusters, Wasabi covers Hot Cloud Storage.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Lambda and Wasabi actually diverge.
Identical on both: free tier (No), user rating (Not yet rated), category (Cloud).
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
- Superclusters
- 1-Click Clusters
- On-demand instances
- Liquid cooling
- InfiniBand networking
- Managed orchestration
- Co-engineering support
Only in Wasabi
- Hot Cloud Storage
- S3 Compatible API
- Object Lock
- Versioning
- Multi-region
- Data Migration Tools
- Immutability
- Ransomware Protection
What people use each for
The jobs each tool is most often brought in to do.
Lambda
- Training foundation models at scale with dedicated GPU infrastructurenot Wasabi
- Large-scale inference serving on enterprise-grade hardwarenot Wasabi
- Multi-GPU distributed training with InfiniBand networkingnot Wasabi
- Single-tenant secure compute for regulated industriesnot Wasabi
- AI lab infrastructure for frontier model developmentnot Wasabi
Wasabi
- Backup and recoverynot Lambda
- Media storagenot Lambda
- Archive replacementnot Lambda
- Ransomware protectionnot Lambda
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
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
Wasabi
- 90-day minimum storage duration with no option to delete before full period without penalty
- Significantly smaller global footprint than AWS with only 16 regions, resulting in higher latency for users in underserved regions
- Performance can degrade with high-volume transactions requiring throughput management strategies
- Hot storage only, no cold/archival storage tier for long-term data at lower cost
- Support responsiveness gaps with teams experiencing multi-day waits for critical issue resolution
Pricing, plan by plan
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
Wasabi
$7.99/monthNo published plan breakdown. See the Wasabi review.
Which should you pick?
Choose Lambda if
- You need superclusters.
- You work on Cloud.
- You also want 1-click clusters.
Choose Wasabi if
- You need hot cloud storage.
- You work on Web, API.
- You also want s3 compatible api.
Questions people ask
- Is Lambda or Wasabi better?
- Neither clearly leads. Lambda starts at On request and Wasabi at $7.99/month, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Lambda or Wasabi?
- Lambda starts at On request and Wasabi at $7.99/month.
- Does Lambda or Wasabi run on more platforms?
- Lambda runs on Cloud. Wasabi runs on Web, API.
- What is Lambda best used for?
- Lambda is most often used for training foundation models at scale with dedicated gpu infrastructure, large-scale inference serving on enterprise-grade hardware, multi-gpu distributed training with infiniband networking, single-tenant secure compute for regulated industries. Of those, training foundation models at scale with dedicated gpu infrastructure and large-scale inference serving on enterprise-grade hardware are not what Wasabi is typically brought in for.
- What can Lambda do that Wasabi cannot?
- Lambda covers Superclusters, 1-Click Clusters, On-demand instances, Liquid cooling. Wasabi covers Hot Cloud Storage, S3 Compatible API, Object Lock, Versioning.
Answered from the vendors’ own pages
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.
SourceWasabi: What is Wasabi's pricing structure?
Wasabi offers pay-as-you-go pricing at $7.99 per TB per month as of July 2026, with no egress or API request fees. Reserved capacity plans are available for multi-year terms with volume discounts.
SourceLambda: 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.
SourceWasabi: Does Wasabi charge for data downloads or API calls?
No. Wasabi includes zero egress fees and zero API request fees, which is a major cost advantage over AWS S3. Customers can plan their budget to the penny without worrying about surprise data transfer charges.
SourceLambda: 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.
SourceWasabi: Is there a minimum storage duration requirement?
Yes. Wasabi enforces a 90-day minimum storage term. Users who delete data before 90 days are still charged for the full 90-day period.
SourceWasabi: Is Wasabi S3-compatible?
Yes. Wasabi Hot Cloud Storage is fully S3-compatible, meaning organizations can integrate it into existing workflows without rewriting application code used with AWS S3.
Related pages
Other head to heads
- Lambda vs Cerebrium
- Lambda vs Beam Cloud
- Lambda vs Fireworks AI
- Lambda vs Anyscale
- Lambda vs IBM Cloud
- Lambda vs OVHcloud
- Lambda vs Oracle Cloud
- Lambda vs Chef
- Lambda vs Koyeb
- Lambda vs AWS (Amazon Web Services)
- Lambda vs Akamai
- Lambda vs Google Cloud Platform
- Lambda vs HAProxy
- Lambda vs kind
- Lambda vs Kustomize
- Lambda vs Linkerd
- Lambda vs DigitalOcean
- Lambda vs Hetzner Cloud
- Lambda vs Scaleway
- Lambda vs Linode
- Lambda vs Vultr
- Lambda vs Zeabur
- Lambda vs Porter
- Lambda vs Contabo
- Lambda vs Encore
- Lambda vs Microsoft Azure
- Wasabi vs Cerebrium
- Wasabi vs Beam Cloud
- Wasabi vs Fireworks AI
- Wasabi vs Anyscale
- Wasabi vs IBM Cloud
- Wasabi vs OVHcloud
- Wasabi vs Oracle Cloud
- Wasabi vs Chef
- Wasabi vs Koyeb
- Wasabi vs AWS (Amazon Web Services)
- Wasabi vs Akamai
- Wasabi vs Google Cloud Platform
- Wasabi vs HAProxy
- Wasabi vs kind
- Wasabi vs Kustomize
- Wasabi vs Linkerd
- Wasabi vs DigitalOcean
- Wasabi vs Hetzner Cloud
- Wasabi vs Scaleway
- Wasabi vs Linode
- Wasabi vs Vultr
- Wasabi vs Zeabur
- Wasabi vs Porter
- Wasabi vs Contabo
- Wasabi vs Encore
- Wasabi vs Microsoft Azure

