Cloud · head to head
Anyscale vs Caddy

Anyscale
Cloud
Platform for scaling AI and data workloads on Ray, built by Ray's creators
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Anyscale pricing for high-end H100/B200-class GPUs is not published and requires contacting sales.; Caddy smaller ecosystem than Nginx, so third-party guides and modules are fewer
- They diverge on capability: Anyscale covers Distributed model training, Caddy covers Automatic HTTPS.
Where they differ
Only the attributes on which Anyscale and Caddy 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 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 Caddy
- Automatic HTTPS
- Caddyfile
- Reverse proxy
- Single binary
What people use each for
The jobs each tool is most often brought in to do.
Anyscale
- Training large models on distributed GPU clustersnot Caddy
- Running batch inference and embedding jobsnot Caddy
- Preparing multimodal datasets at scalenot Caddy
- Post-training LLMs with reinforcement learning frameworksnot Caddy
Caddy
- Sites and services where expired certificates have caused outages beforenot Anyscale
- Small deployments where Nginx configuration is more effort than the problem warrantsnot Anyscale
- Reverse proxying internal services with TLS without a certificate workflownot 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.
Caddy
- Smaller ecosystem than Nginx, so third-party guides and modules are fewer
- Adding plugins means rebuilding the binary rather than loading a module
- Under very high throughput Nginx generally still benchmarks ahead
- Automatic certificate issuance needs outbound internet access, which complicates air-gapped deployments
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
Caddy
Free- CaddyFree
- Full functionality
- Commercial use permitted
- Community support
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.
Choose Caddy if
- You need automatic https.
- You want to start without paying.
- You work on Linux, macOS, Windows, Docker.
- You also want caddyfile.
Questions people ask
- Is Anyscale or Caddy better?
- Neither clearly leads. Anyscale starts at Free and Caddy at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Anyscale or Caddy?
- Anyscale starts at Free and Caddy at Free.
- Does Anyscale or Caddy run on more platforms?
- Anyscale runs on web, api. Caddy runs on Linux, macOS, Windows, 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 Caddy is typically brought in for.
- What can Anyscale do that Caddy cannot?
- Anyscale covers Distributed model training, Multimodal data curation, Batch embedding generation, Multi-cloud orchestration. Caddy covers Automatic HTTPS, Caddyfile, Reverse proxy, Single binary.
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.
SourceCaddy: Is Caddy free?
Yes, open source under the Apache 2.0 licence, free for commercial use.
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.
SourceCaddy: What does automatic HTTPS mean?
Caddy obtains certificates from Let’s Encrypt or ZeroSSL on first request and renews them before expiry, with no cron job or configuration.
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.
SourceCaddy: Caddy or Nginx?
Caddy is dramatically simpler to configure and removes certificate management. Nginx has the larger ecosystem and better peak throughput.
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.
SourceRelated pages
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