Banana AI - GPUs For Inference

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Banana AI Brief overview

Banana.dev is an inference hosting platform built for high‑throughput AI workloads. It provides autoscaling GPUs, pass‑through (at‑cost) compute pricing, and a full “DevOps batteries‑included” experience—GitHub integration, CI/CD, CLI, rolling deploys, tracing, logs, and analytics. Deploy model servers using Banana’s open‑source Potassium HTTP framework and expose them as production endpoints.

How‑to‑use

1. Prepare your model server with Potassium (define an init to load the model and a request handler).
2. Create a Banana project and connect your GitHub repo; Banana builds and deploys the container.
3. Optionally use the Banana CLI to init, develop, and deploy from your local folder.
4. Scale automatically as traffic rises; Banana manages GPU replicas.
5. Call your endpoint from your app and monitor logs, latency, and request analytics in the dashboard.

Banana AI Key features & functions

• Autoscaling GPUs for high‑throughput inference.
• Pass‑through pricing (no markup on GPU time).
• Observability: real‑time traffic, latency, errors; logging + search.
• Business & request analytics to track spend and usage.
• Automation API, SDKs, and CLI for deployment workflows.
• GitHub integration & CI/CD, rolling deploys, environments, and branch deployments.
• Custom GPU types and utilization‑based autoscaling.
• Potassium framework for model serving (open source).

Pricing

• Team — $1,200/month + at‑cost compute: up to 10 team members, 5 projects, 50 max parallel GPUs, custom GPU types, logging + search, utilization‑based autoscaling, request/business analytics, branch deployments, and environments.
• Enterprise — Custom + at‑cost compute: everything in Team, plus SAML SSO, Automation API, higher parallel GPU limits, customizable inference queues, build‑pipeline GPUs, and dedicated support.

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