AI Infrastructure & MLOps Freemium

BentoML

Open-source inference platform for serving models across cloud and private infrastructure

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PricingFreemium
Starting price$0.0484/CPU-hr
Free planYes
Free trialYes
APIYes
Open sourceYes
DeploymentHybrid
Last verifiedAugust 3, 2026
Overview

Tool overview

BentoML is listed under AI Infrastructure & MLOps AI tools.

Summary

What is BentoML?

BentoML packages models and inference code into production services. The Apache-2.0 project supports local and self-hosted deployments, while the managed Bento platform provides autoscaling compute, monitoring, and cloud or private-environment deployment. BentoML joined Modular in February 2026 and continues as an active project.

Best fit

Best for

AI teams deploying custom models with control over infrastructure

Audience

Who is it for?

AI engineersML engineersPlatform teamsEnterprise infrastructure teams
Recommendation

Decision note

Rebuilt from the original export under the complete V412/V411 factual-source-verification workflow. Preview only. Apply remains blocked until Failures = 0, Warnings = 0, Unmapped = 0, Missing = 0; explicit clears are reviewed; image import is disabled or V380 accepts the asset; a representative WordPress edit screen is compared with the export and proposed row; and a post-Apply zero-change Preview succeeds.

Capabilities

Key features

Python-first inference service framework

Autoscaling CPU and GPU deployments

Local, cloud, BYOC, and on-prem paths

Monitoring, logging, APIs, and CI/CD

Workflows

Use cases

Serve custom ML models

Deploy open-source LLMs

Build multimodel inference pipelines

Operate batch or real-time inference

Strengths

Pros

  • Apache-2.0 open-source framework
  • Managed and private deployment choices
  • Per-second active-compute billing
Considerations

Cons

  • Production optimization still needs engineering
  • Managed GPU costs rise with sustained load
  • Acquisition integration may change commercial packaging
Considerations

Limitations

Model quality, safety, latency, and cost remain the operator’s responsibility.

Private deployments require capacity planning, security controls, monitoring, and upgrades.

Cost

Pricing details

Pricing modelFreemium
Starting price$0.0484/CPU-hr
Free planYes
Free trialYes
Pricing context

Billing options

Open source freePay as you goCommitted useEnterprise custom
Pricing context

Pricing note

The open-source framework is free. Managed Starter is pay-as-you-go with one-time free compute credit. CPU begins at $0.0484/hour; T4 is $0.51/hour, L4 $0.80/hour, H100 $2.65/hour, H200 $2.90/hour, and B200 $4.20/hour.

View official pricing
Compatibility

Supported languages

  • English
Connectivity

Integrations

GitHub Actions

Kubernetes

AWS

GCP

Azure

Docker

Specs

Technical details

PlatformsWeb
Multilingual supportYes
Login requiredNo
Open sourceYes
LicenseApache 2.0
DeploymentHybrid
CompanyModular — BentoML project
Current version1.4.39
Editions / plansFree, Basic, Professional, Organization, and Custom plans
Data confidenceHigh
Last verifiedAugust 3, 2026
Documentation → Source code → Release notes → Data source →
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Answers

Frequently asked questions

BentoML packages models and inference code into production services. The Apache-2.0 project supports local and self-hosted deployments, while the managed Bento platform provides autoscaling compute, monitoring, and cloud or private-environment deployment. BentoML joined Modular in February 2026 and continues as an active…
AI teams deploying custom models with control over infrastructure
The listed pricing model for BentoML is freemium. Pricing can change, so users should verify the latest plan details on the official website.
Yes. The current profile indicates that a free trial is available.
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