Oracle Cloud (GPU) vs Banana
A detailed comparison to help you choose between Oracle Cloud (GPU) and Banana.
Quick Verdict
3.8/5
Oracle Cloud (GPU)
0 reviews
1.2/5
Banana
0 reviews
Oracle Cloud (GPU) is rated higher (3.8 vs 1.2). Oracle Cloud Infrastructure includes an always-free A1 Arm allocation (2 OCPUs + 12 GB RAM since July 2026, halved from 4 OCPUs + 24 GB) and GPU shapes from ~$2/GPU-hour (A10 VM) to $10/GPU-hour (H100/H200) and $14-15 (B200/B300). 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.
Oracle Cloud (GPU) Free A1 Arm instances with optional GPU | Banana DEFUNCT — serverless GPU inference platform sunset Feb 2024, shut down March 31, 2024 | |
|---|---|---|
| Overview | ||
| Rating | 3.8 (0 reviews)✓ | 1.2 (0 reviews) |
| Pricing model | freemium | usage-based (historical; shut down 2024-03-31) |
| Starting price | Free tier available✓ | From $2024/mo |
| Best for | Enterprise and serious training/inference workloads that want bare-metal NVIDIA or AMD GPU clusters at hyperscaler-reliable terms, especially MI300X and A100 value seekers and existing Oracle/database customers | Nobody — the platform shut down on March 31, 2024. Use Replicate, Modal, RunPod, Beam, or Baseten for serverless GPU inference. |
| Features | ||
| IPv6 | ||
| DDoS protection | ||
| Automated backups | ||
| Snapshots | ||
| Managed option | ||
| Bare metal | ||
| GPU available | ||
| S3-compatible | ||
| Hourly billing | ✓ | |
| Free tier | ✓ | |
| Data-center locations | ||
| Regions | 50+ regions across 28 countries (NA, SA, EU, MEA, APAC) | — |
| Tags | ||
| Tags | free tiergpu availableeu datacenterus datacenterapac datacenterapi accessarm processors | gpu availableus datacenterapi access |
| Visit Oracle Cloud (GPU) → | Visit Banana → | |
Oracle Cloud (GPU)
Pros
- + Broadest accelerator lineup of any hyperscaler: NVIDIA Blackwell/Hopper/Ampere plus AMD MI300X/MI355X, VMs and bare metal
- + Below-AWS/Azure on-demand GPU list pricing (H100 $10/GPU-hr, A100 80GB $4, MI300X $6) with published, checkable rates
- + Supercluster-class networking (up to 3,200 Gb/sec RDMA) and large local NVMe per node for training checkpoints
- + Credit-backed compute SLA and a full cloud stack (storage, K8s, databases, S3-compatible object) in 50+ regions
Cons
- - GPU quota and capacity processes can require sales engagement; 8-GPU node minimums on the best shapes
- - OCI console/IAM complexity and thinner community documentation than AWS/GCP
- - The 'up to 220% cheaper' claim is a dated vendor comparison; neoclouds undercut on some shapes
- - Egress, storage, image licensing and commitment terms add to headline GPU rates; free tier is CPU-only
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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