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Cloud · head to head

Anyscale vs Cerebrium

Anyscale logo

Anyscale

Cloud

Platform for scaling AI and data workloads on Ray, built by Ray's creators

From
Free
Rated
-
Full reviewWebsite
Cerebrium logo

Cerebrium

Cloud

Serverless GPU infrastructure for real-time AI inference and applications

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Anyscale pricing for high-end H100/B200-class GPUs is not published and requires contacting sales.; Cerebrium free Hobby tier limited to 3 apps and 5 GPU concurrency
  • They diverge on capability: Anyscale covers Distributed model training, Cerebrium covers Ultra-fast cold starts.

Where they differ

Only the attributes on which Anyscale and Cerebrium actually diverge.

Attributes where Anyscale and Cerebrium differ
AttributeAnyscaleCerebrium
Pricing modelusage-basedFreemium with monthly plans and per-second compute charges
Platformsweb, apiCloud, Docker

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Cloud).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Anyscale

  • Distributed model training
  • Multimodal data curation
  • Batch embedding generation
  • Multi-cloud orchestration
  • Governance and security
  • Observability
  • Bring-your-own-cloud deployment
  • Elastic GPU allocation

Only in Cerebrium

  • Ultra-fast cold starts
  • Elastic scaling
  • Bring your own code
  • Multi-region failover
  • WebSocket and streaming
  • Asynchronous jobs
  • CI/CD with gradual rollouts
  • OpenTelemetry integration

What people use each for

The jobs each tool is most often brought in to do.

Anyscale

  • Training large models on distributed GPU clustersnot Cerebrium
  • Running batch inference and embedding jobsnot Cerebrium
  • Preparing multimodal datasets at scalenot Cerebrium
  • Post-training LLMs with reinforcement learning frameworksnot Cerebrium

Cerebrium

  • Deploying voice agents and conversational AI applicationsnot Anyscale
  • Video and image model serving with low latencynot Anyscale
  • LLM inference and completion endpointsnot Anyscale
  • Real-time embeddings and vector database operationsnot Anyscale
  • Distributed model training with hyperparameter sweepsnot Anyscale

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Anyscale

  • Pricing for high-end H100/B200-class GPUs is not published and requires contacting sales.
  • Built around Ray, so teams not already using Ray face a steeper adoption curve than single-purpose inference APIs.
  • No published fixed-fee subscription tier; all listed pricing is usage-based on-demand compute.

Cerebrium

  • Free Hobby tier limited to 3 apps and 5 GPU concurrency
  • Standard plan at $100/month required for production deployments
  • Per-second compute pricing requires continuous cost monitoring
  • Storage costs add up for large model files

Pricing, plan by plan

Anyscale

Free
  • Pay-as-you-go$undefined/mo
    • CPU only from $0.0135/hr
    • NVIDIA T4 $0.5682/hr
    • NVIDIA L4 $0.9542/hr
  • Committed contract$undefined/mo
    • Volume discounts
    • Use of existing GPU reservations

Cerebrium

Free
  • HobbyFree
    • 3 user seats
    • Up to 3 deployed apps
    • 5 GPU concurrency
  • Standard$100/month
    • Unlimited seats and apps
    • 30 GPU concurrency
    • Custom domains
  • Enterprise$undefined/custom
    • Unlimited resources
    • Volume discounts
    • Dedicated support
  • GPU Compute$undefined/per-second
    • T4: $0.000164/s
    • H100: $0.00167/s

Which should you pick?

Choose Anyscale if

  • You need distributed model training.
  • You want to start without paying.
  • You work on web, api.
  • You also want multimodal data curation.
Anyscale review

Choose Cerebrium if

  • You need ultra-fast cold starts.
  • You want to start without paying.
  • You work on Cloud, Docker.
  • You also want elastic scaling.
Cerebrium review

Questions people ask

Is Anyscale or Cerebrium better?
Neither clearly leads. Anyscale starts at Free and Cerebrium at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Anyscale or Cerebrium?
Anyscale starts at Free and Cerebrium at Free.
Does Anyscale or Cerebrium run on more platforms?
Anyscale runs on web, api. Cerebrium runs on Cloud, Docker.
Can I use Anyscale for free?
Both have a free tier, so you can try either at no cost before committing.
What is Anyscale best used for?
Anyscale is most often used for training large models on distributed gpu clusters, running batch inference and embedding jobs, preparing multimodal datasets at scale, post-training llms with reinforcement learning frameworks. Of those, training large models on distributed gpu clusters and running batch inference and embedding jobs are not what Cerebrium is typically brought in for.
What can Anyscale do that Cerebrium cannot?
Anyscale covers Distributed model training, Multimodal data curation, Batch embedding generation, Multi-cloud orchestration. Cerebrium covers Ultra-fast cold starts, Elastic scaling, Bring your own code, Multi-region failover.

Answered from the vendors’ own pages

Anyscale: How much does Anyscale cost?

Anyscale bills on a pay-as-you-go basis: CPU compute starts at $0.0135/hr, NVIDIA T4 at $0.5682/hr, and NVIDIA A100 at $4.9591/hr, with committed contracts offering volume discounts for larger workloads.

Source
Cerebrium: Is Cerebrium only for inference or can it train models?

Cerebrium supports both inference serving and model training with hyperparameter sweeps. It enables deployment of voice agents, LLMs, video models, and other AI applications.

Source
Anyscale: Is there a free trial or credit?

New users receive $100 in Anyscale credits to explore the platform, which can be applied toward starter templates and on-demand compute usage.

Source
Cerebrium: How do the cold starts compare to other platforms?

Cerebrium achieves 2-4 second cold starts through memory and GPU snapshotting, significantly faster than traditional 30+ second cold boots. This is competitive with platforms like Beam Cloud.

Source
Anyscale: How is usage billed?

Hosted usage is billed hourly per compute instance type and invoiced monthly by credit card; bring-your-own-cloud usage is invoiced through Anyscale or the customer's cloud marketplace account.

Source
Cerebrium: What compliance certifications does Cerebrium have?

Cerebrium maintains SOC 2 Type II compliance, HIPAA certification, GDPR compliance, and ISO certification. It provides gVisor container isolation and configurable data residency for regulated workloads.

Source
Anyscale: What support is included?

Hosted plans include business-hours support with up to 5 case submissions, while bring-your-own-cloud deployments get 24x7 enterprise SLAs and unlimited case submissions.

Source
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