Rafay vs Together AI (2026): Pricing, Features & Verdict
Together AI is our pick, scoring 6.8/10 against 5.9/10 for Rafay on our AI Software criteria. Its biggest advantage: higher Cost score (7/10 vs 2/10). Neither Rafay nor Together AI lists a free plan.
Last updated: November 2026
Rafay
5.9/10
Rafay is a SaaS or self-hosted platform that automates Kubernetes and GPU infrastructure operations across clouds, data centers and edge for enterprises, telcos and neoclouds.
Together AI
6.8/10
Together AI is a cloud platform for running, fine-tuning and training open-source AI models. It offers serverless inference, dedicated endpoints and rentable NVIDIA GPU clusters.
Feature-by-Feature Comparison
| Feature | | |
|---|---|---|
| Scores | ||
| Overall Rating | 5.9/10 | 6.8/10 |
| Integration | 7/10 | 7/10 |
| Analytics | 6/10 | 5/10 |
| Customization | 7/10 | 8/10 |
| Ease of Use | 5/10 | 6/10 |
| Support | 7/10 | 5/10 |
| Cost | 2/10 | 7/10 |
| Scalability | 8/10 | 8/10 |
| Security | 8/10 | 7/10 |
| 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 Kubernetes | ||
| Git Deployments | Not listed | |
| Automatic Backups | Not listed | |
| Managed WordPress | Not listed | |
| Cloud Compute | Not listed | |
| Shared Hosting | Not listed | |
Who Rafay and Together AI suit
Rafay fits enterprise better; Together AI fits startups and developers better.
| Audience | Rafay | Together AI |
|---|---|---|
| Startups | 2/10The minimum published marketplace contract and the governance-heavy design are too much for small teams with few clusters. | 8/10Pay-as-you-go token pricing and preemptible GPUs make it cheap for AI startups to get started. |
| Developers | 5/10It gives developers self-service and GitOps access, but reviewers say its restrictions can slow developer workflows. | 9/10It is API-first and gives developers OpenAI-style access to many open models plus GPU clusters. |
| Enterprise | 9/10Contract pricing starting around $240,000 a year, fleet governance, and Fortune 50 and large telco customers make it an enterprise product. | 6/10Reserved clusters and SOC 2 Type 2 help, but SemiAnalysis reports reliability complaints on large clusters. |
| Customer Support Teams | Not rated | 2/10Reviewers say non-technical teams would need engineering help to build anything on it. |
| Financial Services | 7/10Customers include MoneyGram, and reviewers describe its policy-first approach as suited to regulated sectors such as banking. | Not rated |
| Healthcare | 6/10Guardant Health and Amgen appear as customers, and SOC 2 Type II covers the hosted service. | Not rated |
| IT Teams | 8/10Central platform and IT operations teams use it to standardize and govern many Kubernetes clusters across clouds and data centers. | Not rated |
Which One Should You Choose?
Why choose Rafay
- Higher Support score (7/10 vs 5/10)
- Higher Analytics score (6/10 vs 5/10)
- Better fit for enterprise (9/10 vs 6/10)
Why choose Together AI
- Higher Cost score (7/10 vs 2/10)
- Higher Customization score (8/10 vs 7/10)
- Better fit for startups (8/10 vs 2/10)
- Better fit for developers (9/10 vs 5/10)
Pros & Cons
Rafay
Pros
- Manages lifecycle, policy and access for clusters on EKS, AKS, GKE, OKE, private clouds and on-premises from one console, which reviewers value most.
- Role-based and zero-trust access lets teams work on clusters without passing kubeconfig files around.
- Usage billing is based on running averages with a true-up-forward policy, so short spikes in node count are not charged.
- A self-hosted controller and air-gapped deployments are available for sovereign and regulated environments.
- Provides the RCTL CLI, an API and a Terraform provider for platform resources, including backup policies.
- PeerSpot reviewers rated support responsive and knowledgeable.
Cons
- Very expensive for small fleets: the smallest AWS Marketplace bundle is $240,000 for 50 nodes over 12 months.
- Detailed pricing is not public on Rafay's own site, so buyers have to talk to sales.
- Reviewers report a learning curve and documentation that new team members find hard to follow.
- One reviewer reports lag with high-throughput log streaming and Kafka-heavy workloads.
- A competitor's review calls it rigid for developers and overkill for organizations with fewer than about 10 clusters.
- Product documentation sits behind a login, which makes evaluation before purchase harder.
Together AI
Pros
- Low per-token prices on popular open models, for example $0.15 per million input tokens for gpt-oss-120B.
- Preemptible H100s at $1.99 per GPU-hour cut training costs for jobs that can tolerate interruption.
- Instant Clusters can be managed by API, CLI or Terraform, with Slurm and Kubernetes options.
- SemiAnalysis credits its kernel and FlashAttention work with improving performance.
- 24/7 on-call SRE support for cluster customers.
- The company reports a SOC 2 Type 2 examination and says it follows HIPAA requirements.
Cons
- SemiAnalysis reports frequent reliability complaints on clusters of 64 or more GPUs, which led to a downgrade to Silver.
- Kubernetes clusters lack horizontal node autoscaling, and onboarding needs SSH rather than a downloadable kubeconfig.
- Trustpilot reviews cite billing and support problems.
- Usage-metered billing across many services makes monthly costs hard to forecast.
- It requires ML engineering skill, and reviewers note gaps in the documentation.
Not sold on either?
Frequently Asked Questions
Together AI scores higher on our AI Software criteria: 6.8/10 against 5.9/10 for Rafay. The largest gap is in Cost: 2/10 for Rafay and 7/10 for Together AI.
No, neither Rafay nor Together AI lists a free plan.
Together AI is the better fit for startups: we rate it 8/10 for them, against 2/10 for Rafay.
