Anyscale vs Baseten (2026): Pricing, Features & Verdict
Baseten is our pick, scoring 6.8/10 against 6.3/10 for Anyscale on our AI Software criteria. Its biggest advantage: higher Customization score (8/10 vs 7/10). Neither Anyscale nor Baseten lists a free plan.
Last updated: November 2026
Anyscale
6.3/10
Anyscale is a managed platform from the creators of Ray for running distributed AI data processing, training and inference on hosted or customer-owned cloud and Kubernetes compute.
Baseten
6.8/10
Baseten is an AI inference platform that lets engineering teams serve, scale and train open-weight and custom models on managed multi-cloud GPUs, billed per minute.
Feature-by-Feature Comparison
| Feature | | |
|---|---|---|
| Scores | ||
| Overall Rating | 6.3/10 | 6.8/10 |
| Integration | 7/10 | 6/10 |
| Analytics | 7/10 | 7/10 |
| Customization | 7/10 | 8/10 |
| Ease of Use | 5/10 | 6/10 |
| Support | 6/10 | 6/10 |
| Cost | 4/10 | 5/10 |
| Scalability | 9/10 | 9/10 |
| Security | 8/10 | 9/10 |
| Pricing | ||
| Free plan | No | No |
| Cheapest paid plan | Contact for pricing | Contact for pricing |
| Estimated cost for 10 users | Contact for pricing | Contact for pricing |
| Features | ||
| API and CLI | ||
| Managed WordPress | Not listed | |
| Multiple Regions | ||
| Cloud Compute | ||
| Shared Hosting | Not listed | |
| Managed Databases | Not listed | |
| Object Storage | Not listed | |
| Uptime SLA | Not listed | |
| Serverless Functions | Not listed | |
Who Anyscale and Baseten suit
Baseten fits saas companies and startups better than Anyscale.
| Audience | Anyscale | Baseten |
|---|---|---|
| SaaS Companies | 6/10Useful for SaaS companies running batch inference or model serving at scale, though it does not host web front ends, databases or CI/CD. | 9/10Software companies such as Cursor, Notion and Lovable use it to serve AI features in their products. |
| Startups | 6/10The $100 starting credit and pay-as-you-go hosted option help AI startups, but reviewers say costs are hard to predict and the platform can be too much for simple workloads. | 8/10No contract and per-minute billing with scale to zero suit AI startups, though bills can rise fast with traffic. |
| Developers | 8/10Built for ML engineers and Python developers who write Ray code and want managed clusters, workspaces, a CLI and an SDK. | 9/10Built for ML and software engineers who package models with a CLI, config files and Python classes. |
| Enterprise | 8/10BYOC in the customer's own VPC, SSO/SAML/SCIM, audit logs, SOC 2 Type II and ISO 27001, and 24x7 enterprise support suit large AI teams. | 8/10Offers SOC 2 Type II, HIPAA BAAs, single-tenant and self-hosted deployments, BYOK encryption and negotiated SLAs. |
| Small Business | 2/10It is a specialist distributed AI compute platform and offers nothing for typical small business hosting needs. | 2/10Requires ML engineering skills and offers no no-code tools for non-technical teams. |
| Healthcare | Not rated | 7/10Supports HIPAA with a BAA and zero retention for synchronous inference, and is used by clinical AI firms such as Abridge and OpenEvidence. |
Which One Should You Choose?
Why choose Anyscale
- Higher Integration score (7/10 vs 6/10)
Why choose Baseten
- Higher Customization score (8/10 vs 7/10)
- Higher Ease of Use score (6/10 vs 5/10)
- Better fit for saas companies (9/10 vs 6/10)
- Better fit for startups (8/10 vs 6/10)
Pros & Cons
Anyscale
Pros
- Built by the creators of Ray, so existing Ray code scales to large GPU clusters with few changes, a point G2 reviewers also make.
- The BYOC option keeps data and compute inside the customer's own AWS, GCP or Kubernetes environment and can use existing GPU reservations.
- Runs on several compute sources: AWS, GCP, Azure AKS, Nebius, CoreWeave and on-premises Kubernetes.
- Holds SOC 2 Type II and ISO 27001, and offers SSO, SAML, SCIM and audit logs for multi-team governance.
- Usage-based billing with no fixed monthly fee, plus $100 in starting credits for testing.
Cons
- G2 reviewers report a steep learning curve for teams unfamiliar with Ray concepts.
- Costs are hard to forecast, and Spheron estimates managed clusters cost roughly 1.5 to 2 times bare-metal GPU rates.
- Rates for H100 and newer GPUs are not published and require contacting sales.
- The hosted option has limited regions, business-hours support capped at 5 cases, and only temporary 90-day scratch storage.
- It focuses on Ray workloads and does not cover web front ends, databases or CI/CD for full applications.
Baseten
Pros
- Broad compliance coverage: SOC 2 Type II, SOC 3, HIPAA with a BAA, GDPR and PCI DSS, plus BYOK encryption for model weights and payloads.
- Flexible deployment: the same stack runs on Baseten's multi-cloud pool, on single-tenant clusters, or in a self-hosted data plane inside your own VPC.
- Per-minute GPU billing and scale to zero (min replicas defaults to 0) mean idle dev deployments cost nothing.
- Wide range of GPUs, from T4 at about $0.63 an hour to B200 at about $9.98 an hour, with failover across 20+ cloud providers.
- Built-in logs, metrics and traces for every dedicated deployment, exportable to Datadog, Prometheus, Grafana and New Relic.
Cons
- Covers inference, training and sandboxes only, so databases, object storage and general app hosting need another provider.
- Dedicated replicas bill per minute while they run, including cold-start time and the default 15-minute scale-down delay, which can make bills hard to predict.
- Built for ML engineers. Reviewers say non-technical teams will struggle, and performance tuning still needs ML expertise.
- Very few independent reviews: G2 lists too few reviews to give buying insight.
- SLAs, reserved capacity and volume discounts are only available through negotiated contracts with sales.
Not sold on either?
Frequently Asked Questions
Baseten scores higher on our AI Software criteria: 6.8/10 against 6.3/10 for Anyscale. The largest gap is in Cost: 4/10 for Anyscale and 5/10 for Baseten.
No, neither Anyscale nor Baseten lists a free plan.
Baseten is the better fit for saas companies: we rate it 9/10 for them, against 6/10 for Anyscale.
