兩者的成長率相比如何？

Nebius 的月增率為 +10.7%；Qubinets 為 0%。

價格相比如何？

Nebius：付費、需聯絡報價。Usage-based pricing published on the site. On-demand GPU instances range from roughly $1.55/GPU-hour for L40S up to about $9.50/GPU-hour for HGX B300, with preemptible and live spot options starting around $0.79/GPU-hour. CPU-only instances start near $0.06/cpu-hour, managed Kubernetes and networking are free, and large-scale clusters or commitments are quoted through sales. Qubinets：免費增值。Freemium with paid and enterprise/managed tiers. A free or open-source core is offered, with paid plans and contact-based enterprise options layered on top. Because the site was unreachable during this audit, confirm exact pricing directly with the vendor.

Nebius 與 Qubinets 有哪些替代方案？

相關分類中的其他工具包括 fal.ai, RunPod, Together AI, Vast.ai, Modal。

Nebius vs Qubinets — 流量 (114.57萬 vs 802)、定價與選型結論

Open AI Tools

Nebius vs Qubinets — 流量 (114.57萬 vs 802)、定價與選型結論 | Open AI Tools

流量與規格並排比較表

面向／指標	Nebius	Qubinets
官方網域	nebius.com	qubinets.com
定價模式	付費、需聯絡報價	免費增值
每月造訪次數	114.57萬 (1,145,711)	802 (802)
月流量變化量	+11.08萬 (+10.7%)	+802 (0%)
主要市場與市佔	🇺🇸 美國 (46.8%)	🇹🇭 泰國 (100%)
每月直接造訪	44.79萬	334
使用者評分	4.5	4
支援平台	網站	網站

Nebius

Nebius is an AI-focused cloud platform that gives teams non-virtualized NVIDIA GPU clusters, managed MLOps tooling, and a serverless inference layer so they can move from experiment to production on one stack.

Non-virtualized GPU clusters

Bare-metal access to NVIDIA GB300, B300, GB200, B200, H200, H100, RTX PRO 6000, and L40S GPUs connected over InfiniBand for training and inference at scale.

Nebius Token Factory

A managed inference service for running popular open and frontier models through an API, so applications can add LLM capabilities without owning GPUs.

Managed MLOps services

Built-in Kubernetes, Soperator for Slurm jobs, PostgreSQL, and MLflow give teams a ready-made environment for orchestration, tracking, and experiments.

Flexible consumption and spot pricing

Choose on-demand, preemptible, or live market-driven spot capacity, or commit to reserved clusters for discounts on long-running workloads.