BentoML

What is BentoML?

BentoML is the company behind an open-source model-serving library and the Bento Inference Platform, built for teams that need to run AI models in production. You can launch popular open models such as Llama 4, DeepSeek, Qwen, Flux and GPT-OSS from a catalog, or package a custom or fine-tuned model of any framework with the BentoML Python library and engines like vLLM, SGLang or TRT-LLM. The platform provides autoscaling with scale-to-zero, fast cold starts, cloud development environments, an LLM gateway, canary and A/B releases with rollbacks, and observability. Workloads can run on Bento Cloud GPUs, in your own AWS, GCP or Azure account, on Kubernetes or on premises. Billing is metered by the second, and deployments scaled to zero incur no cost. The pricing page lists Pay As You Go, Committed Use Discount and Custom tiers, with GPU rates such as $0.51 / hr for an Nvidia T4. A free trial gives a one-time compute credit.

Use cases

• Deploy open-source LLMs
• Package custom models for serving
• Autoscale GPU inference
• Run inference in your own VPC
• Batch process large datasets
• Chain models into RAG workflows

Who it's for

• ML engineers
• AI platform teams
• Backend developers

Why use BentoML

• You can start with a catalog model and move to a custom one without changing platforms.
• Scale-to-zero and per-second metering mean idle deployments incur no compute cost.
• Running in your own VPC or on premises keeps control over data and network policies.
• The open-source library lets you package the same model locally before deploying.
• Release tools such as canary and rollback make production changes safer.

BentoML features

• Open model catalog with day-one model access
• Python library for packaging models of any framework
• Autoscaling with scale-to-zero and fast cold starts
• Per-second metering of active compute
• Bring-your-own-cloud on AWS, GCP and Azure
• LLM gateway with one API across providers
• Canary, shadow and A/B releases with rollbacks
• Cloud development codespace for GPU runs
• Monitoring with LLM-specific metrics
• Batch, async and interactive serving patterns
• SOC 2 Type II compliance

BentoML integrations

• vLLM
• TRT-LLM
• SGLang
• PyTorch
• JAX
• Transformers
• Hugging Face
• Kubernetes

How to get started with BentoML

1. Sign up and use the one-time free compute credit to try a deployment.
2. Pick a model from the open catalog or package your own with the BentoML library.
3. Choose GPUs, autoscaling rules and where the deployment will run.
4. Deploy from the web console or CI/CD and check the hourly rate estimate.
5. Monitor performance and scale as traffic grows.

BentoML limitations

• Pay As You Go plan has community Slack support only
• Starter plan requires a credit card to unlock more GPU types
• Enterprise BYOC setup takes hours and on-premises takes 1 to 2 weeks
• Requires engineering knowledge of model serving

BentoML pricing

BentoML has no free plan, but it offers a free trial.

BentoML plans

• Pay As You Go

  Price on vendor site

  Per-second compute metering

  • Dedicated deployments
  • Fast cold start and auto-scaling
  • SOC 2 Type II compliant
  • Community Slack support

• Committed Use Discount

  Price on vendor site

  • Priority access to H100 and H200
  • Unlimited seats and deployments
  • Dedicated compute pool
  • Dedicated Slack channel

• Custom

  Custom

  • Full control in your VPC or on-prem
  • Custom SLAs
  • Audit logs and SSO
  • Dedicated support engineering

Plans as listed on the official pricing page on 24 Oct 2026. Prices can change and may vary by country or exclude tax. Check the official pricing page.

BentoML alternatives

The main BentoML alternatives listed on Debuly are Baseten, Modal, Replicate, Together AI, vLLM and Fireworks AI. The table compares pricing and platforms; order is A–Z.

1. 

   Baseten

   Inference platform for deploying open-source, custom and fine-tuned AI models, with per-token Model APIs and dedicated GPUs.

   Developer platforms
   PaidVisit Baseten (official site)
2. 

   Fireworks AI

   Inference and training platform for open models: pay-per-token serverless APIs, GPU deployments, fine-tuning and reserved capacity.

   Developer platformsCodingAutomation and agents
   PaidVisit Fireworks AI (official site)
3. 

   Modal

   Serverless cloud platform for running AI inference, training, batch jobs and agent sandboxes, billed per second of compute.

   Developer platformsAutomation and agentsCoding
   FreemiumVisit Modal (official site)
4. 

   Replicate

   Cloud API for running, fine-tuning and deploying open-source and proprietary AI models, billed by compute time or by output.

   Developer platformsImage generationVideo
   PaidVisit Replicate (official site)
5. 

   Together AI

   AI cloud for running open-source models through serverless and batch inference, dedicated endpoints, GPU clusters and fine-tuning.

   Developer platformsCoding
   PaidVisit Together AI (official site)
6. 

   vLLM

   Open-source engine for serving LLMs with PagedAttention, continuous batching and an OpenAI-compatible API.

   Developer platformsCoding
   Open sourceVisit vLLM (official site)

BentoML FAQ

Sources & verification

Facts on this page come from the official sources below, each with the date we read it. Written by Debuly; the vendor did not review this page.

Image credits

• Logo: from bentoml.com · fetched 23 Oct 2026 · Vendor trademark, used only to identify the product; removed on request
• Cover: none collected yet, so a generated tile is shown.

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