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General AI agent that executes multi-step tasks end to end — research, slides, design, browsing — instead of only answering questions.
Enterprise unified API gateway giving one integration point to 100+ LLMs like Claude, GPT, and Gemini with reliability guarantees.
Unified pay-per-use API serving 400+ multimodal AI models (image, video, audio, 3D, LLM) through one OpenAI-compatible key.
GPU rental marketplace with per-second billing across thousands of GPUs, aimed at AI training, inference, and fine-tuning workloads.
Serverless AI cloud for running inference, training and sandboxes on GPUs with fast cold starts and pay-per-use billing.
No public pricing
No public pricing
No public pricing
- ✦Autonomous multi-step task execution
- ✦Website and app building
- ✦AI slides, design and image generation
- ✦Manus browser operator
- ✦Wide Research mode
- ✦Cross-platform web, desktop and mobile apps
- ✦Unified API for 100+ AI models
- ✦Intelligent request routing across models
- ✦AI Model Insurance for quality/reliability guarantees
- ✦Enterprise-focused LLM access layer
- ✦400+ AI models via one unified API
- ✦Multimodal coverage: image, video, audio, 3D, LLM
- ✦On-demand, pay-per-use pricing
- ✦Day-0 access to new state-of-the-art models
- ✦OpenAI-compatible single key
- ✦SOC 2 and HIPAA compliance, 99.99% uptime
- ✦On-demand GPU cloud with per-second billing
- ✦Interruptible instances at discounted rates for batch/fault-tolerant jobs
- ✦Reserved capacity with 1, 3, or 6-month terms for steady workloads
- ✦Serverless deployment with autoscale-to-zero for inference endpoints
- ✦Dedicated multi-node clusters with InfiniBand for large-scale training
- ✦Python SDK and CLI plus REST API for programmatic provisioning
- ✦Access to 68+ GPU types across 40+ data centers
- ✦Pre-configured templates for popular open-source models
- ✦Serverless GPU compute defined in Python
- ✦Sub-second container cold starts
- ✦Autoscale 0 to 1000+ GPUs
- ✦Inference, training and batch workloads
- ✦Secure sandboxes for untrusted code
- ✦Built-in logging and observability
- →Automate end-to-end digital tasks
- →Produce websites and presentations
- →Conduct broad research
- →Hand off browser tasks to an agent
- →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
- →Integrate video and image generation
- →Access many LLMs through one API
- →Build multimodal AI applications
- →Batch generate and prototype cheaply
- →ML engineers training or fine-tuning models on rented GPUs
- →Startups running inference at scale without owning hardware
- →Developers needing quick, low-cost access to specific GPU types
- →Teams building AI agents that autonomously provision compute
- →Deploying and scaling model inference
- →Fine-tuning and training models
- →Running batch/parallel AI jobs
- →Executing untrusted code in sandboxes