兩者的成長率相比如何？

Nebius 的月增率為 +10.7%；Rivet.dev 為 -44.3%。

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. Rivet.dev：免費增值、需聯絡報價。Rivet Cloud 採用 "方案 + 節點" 的計費模式。控制平面免費（0 美元）用於原型驗證，Hobby 每月 10 美元，Team 每月 120 美元，Enterprise 每月 900 美元，分別提升控制平面備援、Actor Node 上限與支援等級。Actor Node 額外按月計費，從 4.20 美元（R-5）到 94.50 美元（R-160）。自架基於 Apache 2.0 免費開源，來自 Y Combinator 或 a16z Speedrun 的新創公司可獲得 Team 方案 12 個月五折優惠。

Nebius 與 Rivet.dev 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 Rivet.dev — 流量 (114.57萬 vs 2.14萬)、定價與選型結論

Open AI Tools

Nebius vs Rivet.dev — 流量 (114.57萬 vs 2.14萬)、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	Rivet.dev
官方網域	nebius.com	rivet.dev
定價模式	付費、需聯絡報價	免費增值、需聯絡報價
每月造訪次數	114.57萬 (1,145,711)	2.14萬 (21,359)
月流量變化量	+11.08萬 (+10.7%)	-1.7萬 (-44.3%)
主要市場與市佔	🇺🇸 美國 (46.8%)	🇺🇸 美國 (39.4%)
每月直接造訪	44.79萬	1.07萬
使用者評分	4.5	4.5
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.