Lambda vs Banana
A detailed comparison to help you choose between Lambda and Banana.
Quick Verdict
3.7/5
Lambda
0 reviews
1.2/5
Banana
0 reviews
Lambda is rated higher (3.7 vs 1.2). Lambda is a GPU cloud for training and running AI models, offering on-demand NVIDIA GPU instances and reserved clusters for AI teams and researchers. Banana was an ML inference hosting platform (Docker-based, Potassium framework). The service shut down permanently on March 31, 2024; do not purchase. Alternatives: Replicate, Modal, RunPod, Beam, Baseten.
Lambda On-demand GPU cloud for ML training and inference | Banana DEFUNCT — serverless GPU inference platform sunset Feb 2024, shut down March 31, 2024 | |
|---|---|---|
| Overview | ||
| Rating | 3.7 (0 reviews)✓ | 1.2 (0 reviews) |
| Pricing model | usage-based | usage-based (historical; shut down 2024-03-31) |
| Starting price | From $0.69/mo✓ | From $2024/mo |
| Best for | ML researchers and engineering teams optimizing cost per GPU-hour for training, fine-tuning, and batch inference who can tolerate best-effort capacity. | Nobody — the platform shut down on March 31, 2024. Use Replicate, Modal, RunPod, Beam, or Baseten for serverless GPU inference. |
| Specifications (entry plan) | ||
| CPU cores | 14 vCPU | — |
| RAM | 46 GB | — |
| Storage | — | — |
| Bandwidth | — | — |
| SLA uptime | — | — |
| Data-center count | 14 | — |
| €/vCPU/mo | €0.05 | — |
| €/GB RAM/mo | €0.01 | — |
| Features | ||
| IPv6 | ✓ | |
| DDoS protection | ✓ | |
| Automated backups | ||
| Snapshots | ||
| Managed option | ||
| Bare metal | ||
| GPU available | ||
| S3-compatible | ||
| Hourly billing | ✓ | |
| Free tier | ||
| Data-center locations | ||
| Regions | [US x10 regions, Tokyo, Osaka, India, Germany, Israel] | — |
| Tags | ||
| Tags | hourly billinggpu availableus datacenterapi access | gpu availableus datacenterapi access |
| Visit Lambda → | Visit Banana → | |
Lambda
Pros
- + Published per-minute GPU pricing with no egress fees
- + Preinstalled ML stack (Lambda Stack) on all images
- + Full cloud API for instance automation
- + Free egress keeps large checkpoint downloads cheap
- + Cluster tier scales from 16 to 2,000+ GPUs for distributed training
Cons
- - No published uptime SLA for on-demand instances
- - Popular H100 configurations sell out regularly
- - One European region (Germany); no Latin America or Australia
- - No managed databases, snapshots, or backup products
- - Filesystem billing continues after instance deletion
Banana
Pros
- + Historical: developer-friendly Docker/Potassium deployment with scale-to-zero GPU autoscaling
- + Historical: per-second GPU billing with no charge while idle
- + Historical: warm pools and model caching reduced cold starts for popular models
- + The founder published an unusually candid shutdown account and migration guidance
Cons
- - Permanently shut down on March 31, 2024 — the service cannot be purchased or used
- - Pricing was opaque even while alive ($1,200/month Team tier, per-GPU costs unpublished)
- - No published uptime SLA and no independent benchmarks
- - Startup platform risk realized: GPU economics forced closure within two months' notice
- - Third-party listings of its pricing and features conflict and cannot be verified against a live product
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