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Banana

Serverless GPU inference platform for deploying AI models as APIs.

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About

Banana is a serverless GPU platform for hosting AI models as API endpoints. Developers package a model as a Docker container, and Banana handles GPU provisioning, autoscaling, and usage metering, billing per GPU-second with no charge when idle. It supports any model that can be containerized, from LLMs to Stable Diffusion to Whisper.

The platform includes GitHub integration, CI/CD, a CLI, rolling deployments, and built-in performance monitoring. By scaling from zero to as many replicas as needed and back, Banana targets teams that want production inference without managing GPU fleets or Kubernetes.

What it can do

  • Serverless GPU autoscaling
  • Per-second billing, no idle charges
  • GitHub integration and CI/CD
  • Built-in monitoring and tracing
  • Templates for common models

Setup

Sign up at banana.dev, package your model as a Docker container, and deploy via the dashboard or CLI.

Prerequisites

A containerized ML model; familiarity with Docker.

Use cases

model-deploymentgpu-inferencemlopsserverless

Works with

Trust score — 7/10

/10 trustMetrics-checked

Scored 7/10 (metrics tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 126; Trending score 72/100 from researcher assessment.

Sources

Every fact above was checked against these sources. Where a claim comes from the provider and couldn't be independently verified, the text says so.