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Head-to-head · AI Model Hosting

Baseten vs Cerebrium

  • 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
Cerebrium #9 in AI Model Hosting 8.5/10 Free plan Free plan✓ 4 of 4 features Visit Cerebrium

Baseten leads on 0 checks, Cerebrium 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 8.5 out of 10; our editors rank them #1 and #9.

On deployment mode, Baseten gives you Both where Cerebrium offers Serverless.

Baseten is the better fit for teams wanting managed model APIs. Cerebrium is the better fit for teams needing serverless multi-region inference.

  • Baseten fits best

    Teams wanting managed model APIs

  • Cerebrium fits best

    Teams needing serverless multi-region inference

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Side by side

Feature Baseten 9.4/10 Visit ↗ Cerebrium 8.5/10 Visit ↗
At a glance
Editor score 9.4 8.5
Ranking #1 in AI Model Hosting #9 in AI Model Hosting
Best for Teams wanting managed model APIs Teams needing serverless multi-region inference
Pricing model Free plan + paid Free plan + paid
Starting price — $100/mo
Free plan ✓ ✓
Free trial — —
Deployment Cloud, Self-hosted Cloud
Platforms Web Web
Support Email, Live chat, Docs Live chat, Community, Docs
Compliance SOC 2, GDPR, HIPAA, SSO/SAML SOC 2, HIPAA, GDPR, ISO 27001
Built for Small business, Mid-market, Enterprise Small business, Mid-market, Enterprise
Features Baseten 4/4 · Cerebrium 4/4
Autoscaling ✓ ✓
GPU accelerators ✓ ✓
Private deployment ✓ ✓
Batch inference ✓ ✓
Specs
Deployment mode Both Serverless
Supported model formats Truss/Python, custom Docker, vLLM, SGLang, Ollama PyTorch, ONNX, TensorRT, CTranslate2
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 CPU and GPU deployments with configurable autoscaling
  • REST, streaming, WebSocket, async, and OpenAI-compatible endpoints
  • Multi-region controls, batching, Docker deployment, and OpenTelemetry support
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
  • Usage-based CPU, GPU, memory, and storage charges require cost monitoring
  • Hobby limits teams to 3 seats and up to 3 deployed applications
  • Standard adds a $100 monthly fee before metered compute charges
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 →

Cerebrium is a cloud platform for deploying, serving, and scaling AI workloads such as large language models, voice agents, video models, embeddings, and batch jobs. It is aimed at developers and teams running production AI applications…

Read the review →
  1. BasetenAI Model Hosting 9.4Free plan
  2. CerebriumAI Model Hosting 8.5Free 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

  • Cerebrium — where it wins

    • Serverless CPU and GPU deployments with configurable autoscaling
    • REST, streaming, WebSocket, async, and OpenAI-compatible endpoints
    • Multi-region controls, batching, Docker deployment, and OpenTelemetry support

    Where it doesn't

    • Usage-based CPU, GPU, memory, and storage charges require cost monitoring
    • Hobby limits teams to 3 seats and up to 3 deployed applications
    • Standard adds a $100 monthly fee before metered compute charges

More comparisons

All AI model hosting comparisons → · Full ranking →

Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

Last updated · How we research and update