# Baseten vs Ray

**Leader by Vioscale score:** Baseten

| Attribute | Baseten | Ray |
|---|---|---|
| **Vioscale score** | 76.3 (73% (medium)) | 66.8 (68% (medium)) |
| activity.commits_last_30d | - | 100 |
| adoption.dependent_repos | - | 3,641 |
| adoption.github_stars | - | 43,612 |
| adoption.package_downloads_weekly | - | 11,291,327 |
| deployment.options | `{"cloud":true,"hybrid":true,"on_prem":true,"self_hosted":true}` | `{"cloud":true,"hybrid":true,"on_prem":true,"self_hosted":true}` |
| description.long | An infrastructure platform that handles serving, optimizing, and scaling machine learning models across multiple clouds. Offers both managed cloud and self-hosted deployment options with built-in performance tuning, autoscaling, and 99.99% uptime reliability. | Ray is an open-source unified framework for scaling Python and machine learning applications across any infrastructure. It provides distributed compute primitives, specialized AI libraries for data processing, model training, tuning, and serving, with seamless scaling from development environments to large clusters. |
| features.capabilities | `{"role":"serving","evaluation":false,"soc2_type_ii":true,"compute_model":"dedicated_gpu_instance","managed_cloud":true,"model_serving":true,"pricing_model":"per_million_tokens","self_hostable":true,"multi_provider":true,"vpc_deployment":true,"otel_compatible":false,"llm_observability":false,"prompt_management":false,"framework_agnostic":true,"experiment_tracking":true,"openai_compatible_rest_api_schema":true,"bring_your_own_weights_byow_hosting":true,"dynamic_batching_and_kv_cache_management":true,"massive_context_window_support_100k_plus":true,"hipaa_baa_compliance_for_medical_inference":true,"multimodal_vision_and_audio_in_out_support":true,"native_function_calling_and_strict_json_mode":true}` | `{"managed_cloud":true,"model_serving":true,"self_hostable":true,"multi_provider":true,"vpc_deployment":true,"framework_agnostic":true,"experiment_tracking":true}` |
| integrations.count | 3 | 17 |
| integrations.list | `[{"name":"Plotly"},{"name":"OpenAI-compatible endpoint"},{"name":"Truss"}]` | `[{"name":"PyTorch"},{"name":"TensorFlow"},{"name":"AIBrix"},{"name":"AReaL"},{"name":"Cosmos Curate"},{"name":"Daft"},{"name":"Data-Juicer"},{"name":"DeltaCAT"},{"name":"Modin"},{"name":"NeMo Curator"},{"name":"NeMo-RL"},{"name":"OpenRLHF"},{"name":"RayDP"},{"name":"ROLL"},{"name":"SkyRL"},{"name":"SLIME"},{"name":"Syftr"},{"name":"verl"},{"name":"vLLM"}]` |
| language.primary | - | Python |
| license.spdx | - | Apache-2.0 |
| market.availability | `{"hqCountry":"US","primaryMarkets":[],"availabilityScope":"global","availableCountries":[],"notAvailableCountries":[]}` | - |
| platform.support | `{"cli":true,"mac":true,"web":true}` | `{"cli":true}` |
| pricing | `{"type":"hybrid","plans":[{"free":true,"name":"Basic","summary":"$0/month base, pay-as-you-go compute","features":["Dedicated deployments","Model APIs","Training","Fast cold starts","SOC 2 Type II and HIPAA compliant","Email and in-app chat support"],"components":[{"kind":"fixed","amount":0,"period":"month","currency":"USD"}],"description":"Deploy custom, fine-tuned, and open-source models with dedicated deployments, model APIs, training, fast cold starts","contactSales":false},{"free":false,"name":"Pro","summary":"Volume discounts available. Custom pricing via quote.","features":["Everything in Basic","Priority access to high-demand GPUs","Dedicated compute","Higher Model API rate limits","Hands-on engineering expertise","Dedicated support on Slack and Zoom"],"description":"Unlimited autoscaling and priority compute access with dedicated compute, higher rate limits, hands-on engineering support","contactSales":true},{"free":false,"name":"Enterprise","summary":"Volume discounts available. Custom pricing via quote.","features":["Everything in Pro","Custom SLAs","Self-host deployments","On-demand flex compute","Use existing cloud commitments","Full control over data residency","Advanced security and compliance","Custom global regions","Advanced RBAC with Teams"],"description":"Full control with custom SLAs, self-hosted deployments, on-demand flex compute, data residency control, and advanced security","contactSales":true}],"summary":"Free tier with pay-as-you-go compute ($0.01/min for basic instances). Pro and Enterprise plans available via quote with volume discounts.","currency":"USD","freeTier":true,"sourceUrl":"https://www.baseten.co/pricing/","retrievedAt":"2026-08-14T09:22:26.114Z","billingPeriods":["month"]}` | `{"type":"free","freeTier":true,"sourceUrl":"https://www.ray.io","retrievedAt":"2026-08-14T16:39:27.110Z"}` |
| pricing.free_tier | yes | yes |
| pricing.model | freemium | commercial |
| pricing.price_level | low | free |
| pricing.transparent | yes | - |
| release.cadence_days | - | 18 |
| release.history | - | `[{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.58.0","date":"2026-08-23T05:42:08Z","type":"stable","version":"ray-2.58.0"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.57.0","date":"2026-08-11T01:15:44Z","type":"stable","version":"ray-2.57.0"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.56.1","date":"2026-07-17T23:19:47Z","type":"stable","version":"ray-2.56.1"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.56.0","date":"2026-06-29T20:32:55Z","type":"stable","version":"ray-2.56.0"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.55.1","date":"2026-04-22T20:24:41Z","type":"stable","version":"ray-2.55.1"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.55.0","date":"2026-04-15T20:34:27Z","type":"stable","version":"ray-2.55.0"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.54.1","date":"2026-03-25T23:37:39Z","type":"stable","version":"ray-2.54.1"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.54.0","date":"2026-02-18T23:44:44Z","type":"stable","version":"ray-2.54.0"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.53.0","date":"2025-12-20T15:16:24Z","type":"stable","version":"ray-2.53.0"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.51.2","date":"2025-11-29T00:40:40Z","type":"stable","version":"ray-2.51.2"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.52.1","date":"2025-11-28T02:23:22Z","type":"stable","version":"ray-2.52.1"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.52.0","date":"2025-11-21T19:10:39Z","type":"stable","version":"ray-2.52.0"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.51.1","date":"2025-11-01T03:27:11Z","type":"stable","version":"ray-2.51.1"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.51.0","date":"2025-10-29T05:33:49Z","type":"stable","version":"ray-2.51.0"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.50.1","date":"2025-10-18T19:21:43Z","type":"stable","version":"ray-2.50.1"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.50.0","date":"2025-10-10T23:06:29Z","type":"stable","version":"ray-2.50.0"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.49.2","date":"2025-09-19T18:10:36Z","type":"stable","version":"ray-2.49.2"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.49.1","date":"2025-09-03T00:44:11Z","type":"stable","version":"ray-2.49.1"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.49.0","date":"2025-08-26T19:52:24Z","type":"stable","version":"ray-2.49.0"},{"url":"https://github.com/ray-project/ray/releases/tag/ray-2.48.0","date":"2025-07-18T22:27:25Z","type":"stable","version":"ray-2.48.0"}]` |
| reliability.sla_pct | 99.99 | - |
| reliability.status_page | yes | yes |
| security.disclosure_policy | yes | - |
| security.gdpr | yes | - |
| security.hipaa | yes | - |
| security.pci | yes | - |
| security.scorecard | - | 5.7 |
| security.soc2 | yes | - |
| security.vulnerabilities | - | `{"count":12,"source":"https://advisories.ecosyste.ms/api/v1/advisories?ecosystem=pypi&package_name=ray&per_page=100","last_12m":6,"max_severity":"CRITICAL"}` |

## Capabilities (MLOps & LLMOps Tools)

| Capability | Baseten | Ray |
|---|:--:|:--:|
| **Core** |  |  |
| Tool role | Model serving | - |
| **Deployment** |  |  |
| Self-hostable / OSS core | ✓ | ✓ |
| Managed cloud available | ✓ | ✓ |
| On-prem / VPC deployment | ✓ | ✓ |
| **Observability** |  |  |
| LLM tracing / observability | ✗ | - |
| Evaluation (offline / LLM-judge / human) | ✗ | - |
| **Dev** |  |  |
| Prompt management + versioning | ✗ | - |
| **Tracking** |  |  |
| Experiment tracking / model registry | ✓ | ✓ |
| **Serving** |  |  |
| Model serving / inference endpoint | ✓ | ✓ |
| **Interop** |  |  |
| OpenTelemetry / OpenLLMetry compatible | ✗ | - |
| Framework-agnostic | ✓ | ✓ |
| **Gateway** |  |  |
| Multi-provider model support | ✓ | ✓ |
| **Data** |  |  |
| No-train-on-customer-data guarantee | - | - |

*Source: Vioscale. Generated 2026-09-01T15:03:07.204Z. "-" = undocumented, not absent.*