Cloud · head to head
Cerebrium vs Thanos

Cerebrium
Cloud
Serverless GPU infrastructure for real-time AI inference and applications
- From
- Free
- Rated
- -

Thanos
Cloud
Highly available Prometheus with long-term object storage
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Cerebrium free Hobby tier limited to 3 apps and 5 GPU concurrency; Thanos several components — sidecar, store, querier, compactor, ruler — each with its own configuration and failure modes
- They diverge on capability: Cerebrium covers Ultra-fast cold starts, Thanos covers Global query.
Where they differ
Only the attributes on which Cerebrium and Thanos actually diverge.
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 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
Only in Thanos
- Global query
- Object storage retention
- Deduplication
- Downsampling
What people use each for
The jobs each tool is most often brought in to do.
Cerebrium
- Deploying voice agents and conversational AI applicationsnot Thanos
- Video and image model serving with low latencynot Thanos
- LLM inference and completion endpointsnot Thanos
- Real-time embeddings and vector database operationsnot Thanos
- Distributed model training with hyperparameter sweepsnot Thanos
Thanos
- Querying metrics across many clusters or regions from one placenot Cerebrium
- Retaining metrics for years without local disk growthnot Cerebrium
- Removing the gap that appears when a single Prometheus instance restartsnot Cerebrium
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
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
Thanos
- Several components — sidecar, store, querier, compactor, ruler — each with its own configuration and failure modes
- The compactor is a common source of operational trouble and must not run twice against the same bucket
- Query latency over object storage is meaningfully higher than local Prometheus
- Object storage costs and API request charges become real at high volume
Pricing, plan by plan
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
Thanos
Free- ThanosFree
- Full functionality
- No usage limits
- Community support
Which should you pick?
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.
Choose Thanos if
- You need global query.
- You want to start without paying.
- You work on Kubernetes, Linux, Docker.
- You also want object storage retention.
Questions people ask
- Is Cerebrium or Thanos better?
- Neither clearly leads. Cerebrium starts at Free and Thanos at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Cerebrium or Thanos?
- Cerebrium starts at Free and Thanos at Free.
- Does Cerebrium or Thanos run on more platforms?
- Cerebrium runs on Cloud, Docker. Thanos runs on Kubernetes, Linux, Docker.
- Can I use Cerebrium for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Cerebrium best used for?
- Cerebrium is most often used for deploying voice agents and conversational ai applications, video and image model serving with low latency, llm inference and completion endpoints, real-time embeddings and vector database operations. Of those, deploying voice agents and conversational ai applications and video and image model serving with low latency are not what Thanos is typically brought in for.
- What can Cerebrium do that Thanos cannot?
- Cerebrium covers Ultra-fast cold starts, Elastic scaling, Bring your own code, Multi-region failover. Thanos covers Global query, Object storage retention, Deduplication, Downsampling.
Answered from the vendors’ own pages
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.
SourceThanos: Is Thanos free?
Yes, open source and CNCF-incubating. Costs are the object storage it uses.
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.
SourceThanos: Does Thanos replace Prometheus?
No. It runs alongside existing Prometheus servers, adding global query, deduplication and long-term storage.
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.
SourceThanos: Thanos or VictoriaMetrics?
Thanos layers onto Prometheus using object storage and is the more established multi-cluster answer. VictoriaMetrics is a separate store aiming at lower resource use and fewer moving parts.
Related pages
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- Thanos vs Pulumi
- Thanos vs Fly.io
- Thanos vs Anyscale
- Thanos vs Fireworks AI
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