Anyscale vs Nebius (2026)
Updated March 10, 2026
Overview
Anyscale is the company behind Ray, the open-source distributed computing framework used by OpenAI, Uber, and Spotify for scaling AI workloads. Anyscale's platform provides managed Ray clusters for distributed training, batch inference, and model serving, making it easy to scale AI applications across hundreds of GPUs.
Nebius (Nasdaq: NBIS) is a major GPU cloud provider spun off from Yandex, offering large-scale NVIDIA GPU clusters for AI training and inference. With data centers in Europe and expanding globally, Nebius provides enterprise-grade AI infrastructure with competitive pricing and dedicated support for large-scale AI workloads.
Strengths and tradeoffs
What each tool does well, and the limitations to keep in mind.
Pros
- Flexible pay-as-you-go with no monthly fees
- Exceptional employee satisfaction (4.5/5 stars)
- Strong company culture and leadership
- Cost-effective LLM endpoints at half proprietary prices
Cons
- Product described as super complex and technical
- Work-life balance concerns from some employees
- Platform still evolving with features in development
Pros
- Massive scale with 2+ GW contracted power, expanding to 3+ GW
- Latest NVIDIA hardware including B200 Blackwell and GB300
- Up to 35 percent savings with reserved capacity
- Strong employee satisfaction (4.5/5) in Amsterdam
Cons
- No free trial makes evaluation difficult without upfront commitment
- Work-life balance concerns cited by some employees
- Over 90 percent Russian language creates barrier for non-Russian speakers
- Newer player compared to established cloud providers
Compare Anyscale and Nebius on your own traffic
Respan lets you trace LLM and agent calls across any model or framework, A/B test prompts on production traffic, and route requests across 1,000+ models through one gateway.
Try Respan free