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Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.

Nebius logo
Nebius
✓ verifiedPaid

AI-focused cloud offering NVIDIA GPU compute, storage and MLOps tooling for training and inference at scale, with usage-based pricing.

678K visits/mo133K saves
Jan.ai logo
Jan.ai
✓ verifiedFree

Open-source desktop app for running AI chat models locally or via APIs, as a private ChatGPT alternative.

378K visits/mo609 saves
Coze logo
Coze
✓ verifiedFreemium

ByteDance's Coze (Kouzi): an all-in-one AI office assistant for writing, slides, sheets, design, podcasts and images.

7.2M visits/mo
MiniMax logo
MiniMax
✓ verifiedFreemium

Chinese AGI company building multimodal LLMs, Hailuo video, speech and music models, plus AI apps and open APIs.

4.6M visits/mo
Pricing
NVIDIA H100: $3.85/GPU-hour on-demand ($2.15 preemptible)
NVIDIA H200: $4.50/GPU-hour on-demand
NVIDIA B200: $7.15/GPU-hour on-demand
Shared filesystem storage: $0.08/GiB per month

No public pricing

No public pricing

Max Token Plan: 119 CNY/mo (frontier models, up to ~7.1B tokens/mo)
Core features
  • NVIDIA GPU instances (H100, H200, B200, GB200)
  • On-demand and preemptible GPU pricing
  • High-performance and object storage
  • Managed Kubernetes and Slurm (Soperator)
  • Serverless and managed inference (Token Factory)
  • MLOps tooling and 24/7 expert support
  • Commitment discounts up to 35%
  • Run open-source LLMs locally
  • Connect to online models (OpenAI, Claude, Gemini)
  • Private, offline-capable AI chat
  • Open source and self-hostable
  • Model library via Hugging Face
  • Cross-platform desktop app
  • AI writing
  • AI presentation/PPT generation
  • AI spreadsheets and tables
  • AI design
  • AI podcast generation
  • AI image generation
  • MiniMax M-series LLMs (M3, 1M context, MSA)
  • Hailuo AI video generation
  • Speech and music generation models
  • MiniMax Code agentic coding tool
  • Consumer apps (Hailuo, Xingye)
  • Open API and Token Plan for developers
Use cases
  • Train large AI/ML models on GPU clusters
  • Run scalable inference workloads
  • Store and manage large training datasets
  • Run Slurm/Kubernetes AI pipelines
  • Private local AI chat
  • Using multiple models in one app
  • Avoiding cloud data sharing
  • Experimenting with open models
  • Drafting documents
  • Building presentations
  • Generating spreadsheets
  • Creating designs and images
  • Producing podcasts
  • Coding and agentic tasks
  • AI video generation
  • Text-to-speech and music creation
  • Building on MiniMax model APIs
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