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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.
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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
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flux context
✓ verifiedFreemium
Commercial all-in-one AI generator bundling many image, video and music models in one credit-based workspace.
527K visits/mo
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ZenMux
✓ verifiedPaid
Enterprise unified API gateway giving one integration point to 100+ LLMs like Claude, GPT, and Gemini with reliability guarantees.
435K visits/mo11K saves
Pricing
No public 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
Basic: $7.90/mo billed annually (4,800 credits/yr)
Pro: $19.90/mo billed annually (19,200 credits/yr)
Ultra: $69/mo billed annually (67,200 credits/yr)
No public pricing
Core features
- ✦Dialogue with GLM large model
- ✦AI search
- ✦AI drawing
- ✦AI reading
- ✦AI-generated video (沉思清影-AI生视频)
- ✦AI-generated PPT
- ✦Data analysis tools
- ✦Code assistance (代码速写)
- ✦Intelligent agents
- ✦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%
- ✦Text-to-image and image editing
- ✦Text-to-video and image-to-video
- ✦AI music generation
- ✦30+ integrated models
- ✦Image and video upscaling
- ✦Templates and multi-language UI
- ✦Unified API for 100+ AI models
- ✦Intelligent request routing across models
- ✦AI Model Insurance for quality/reliability guarantees
- ✦Enterprise-focused LLM access layer
Use cases
- →Engaging in conversations with an AI model
- →Generating images and videos using AI
- →Creating presentations with AI assistance
- →Analyzing data with AI tools
- →Assisting with code development
- →Train large AI/ML models on GPU clusters
- →Run scalable inference workloads
- →Store and manage large training datasets
- →Run Slurm/Kubernetes AI pipelines
- →Generating images, video and music in one place
- →Editing and style-transferring images
- →Producing marketing and social content
- →Upscaling media to higher resolution
- →Building applications that need failover across multiple LLM providers
- →Consolidating billing/access to many AI models under one API
- →Enterprises requiring guaranteed model output reliability
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