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Head-to-head · AI Model Hosting

Baseten vs Beam

  • Updated Oct 2026
  • Both researched from official sources
  • 5 checks side by side
Higher score Baseten #1 in AI Model Hosting 9.4/10 Free plan Free plan✓ 4 of 4 features Visit Baseten
Beam #10 in AI Model Hosting 8.4/10 Free plan Free plan✓ 4 of 4 features Visit Beam

Baseten leads on 0 checks, Beam on 0, and 5 are even. Who comes out ahead on the 5 yes/no, price and count checks where we have data for both products. The editor score weighs everything else too.

Our verdict

  • Highest scoreBaseten · 9.4/10
  • Free planboth

Baseten scores higher on our rubric for ai model hosting: 9.4 against 8.4 out of 10; our editors rank them #1 and #10.

Baseten is the better fit for teams wanting managed model APIs. Beam is the better fit for developers wanting serverless GPUs and batch jobs.

  • Baseten fits best

    Teams wanting managed model APIs

  • Beam fits best

    Developers wanting serverless GPUs and batch jobs

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Side by side

Feature Baseten 9.4/10 Visit ↗ Beam 8.4/10 Visit ↗
At a glance
Editor score 9.4 8.4
Ranking #1 in AI Model Hosting #10 in AI Model Hosting
Best for Teams wanting managed model APIs Developers wanting serverless GPUs and batch jobs
Pricing model Free plan + paid Free plan + paid
Starting price — $89/mo
Free plan ✓ ✓
Free trial — —
Deployment Cloud, Self-hosted Cloud, Self-hosted
Platforms Web Web
Support Email, Live chat, Docs Live chat, Community, Docs
Compliance SOC 2, GDPR, HIPAA, SSO/SAML SOC 2
Built for Small business, Mid-market, Enterprise Small business, Mid-market, Enterprise
Features Baseten 4/4 · Beam 4/4
Autoscaling ✓ ✓
GPU accelerators ✓ ✓
Private deployment ✓ ✓
Batch inference ✓ ✓
Specs
Deployment mode Both Both
Supported model formats Truss/Python, custom Docker, vLLM, SGLang, Ollama Not checked yet
Deployment regions 2 regions Not checked yet
Our review
Pros
  • OpenAI-compatible Model APIs and dedicated CPU/GPU deployments
  • Autoscaling, async inference, regional endpoints, and observability
  • Training, fine-tuning, custom containers, and self-hosted options
  • Serverless GPU inference with workload-based autoscaling
  • Queues support retries, callbacks, scheduled jobs, and batch processing
  • Cloud, bring-your-own-cloud, and private self-hosted deployment options
Cons
  • Basic includes usage-based compute charges beyond its $0 platform price
  • Regional deployment documentation lists United States and European Union
  • Dedicated Slack and Zoom support is available on Pro rather than Basic
  • Developer limits usage to 5 GPU and 30 CPU containers
  • Monthly plan fees are separate from pay-as-you-go compute charges
  • Growth includes no published monthly price in the available plan details
Our verdict

Baseten is an AI inference platform for teams deploying open-source, custom, and fine-tuned models in production. It combines managed Model APIs with dedicated CPU and GPU deployments, configurable autoscaling, asynchronous inference,…

Read the review →

Beam is a cloud platform for deploying AI inference endpoints, task queues, sandboxes, training jobs, and other GPU workloads. It is designed for developers and engineering teams building AI products without managing traditional cloud…

Read the review →
  1. BasetenAI Model Hosting 9.4Free plan
  2. BeamAI Model Hosting 8.4Free plan

Strengths and trade-offs

  • Baseten — where it wins

    • OpenAI-compatible Model APIs and dedicated CPU/GPU deployments
    • Autoscaling, async inference, regional endpoints, and observability
    • Training, fine-tuning, custom containers, and self-hosted options

    Where it doesn't

    • Basic includes usage-based compute charges beyond its $0 platform price
    • Regional deployment documentation lists United States and European Union
    • Dedicated Slack and Zoom support is available on Pro rather than Basic
  • Beam — where it wins

    • Serverless GPU inference with workload-based autoscaling
    • Queues support retries, callbacks, scheduled jobs, and batch processing
    • Cloud, bring-your-own-cloud, and private self-hosted deployment options

    Where it doesn't

    • Developer limits usage to 5 GPU and 30 CPU containers
    • Monthly plan fees are separate from pay-as-you-go compute charges
    • Growth includes no published monthly price in the available plan details

More comparisons

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

Last updated · How we research and update