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✓ verifiedFreemium
Serverless AI cloud for running inference, training and sandboxes on GPUs with fast cold starts and pay-per-use billing.
988K visits/mo
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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
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BoltAI
✓ verifiedPaid
Native macOS app that unifies 300+ AI models in one private workspace with agents, MCP tools, and one-time licensing.
81K visits/mo33K saves
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Reka Core
✓ verifiedPaid
AI research lab building multimodal 'omni' foundation models and infrastructure aimed at robotics and physical-world applications.
252K visits/mo
Pricing
Starter: $0/mo + compute ($30 free credit)
Team: $250/mo + compute
No public pricing
No public pricing
Essential: $79 (1 seat, one-time)
Pro: $99 (2 seats + 1 mobile, one-time)
Team Perpetual: $99/seat/year
Free trial available
No public pricing
Core features
- ✦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
- ✦LLM API router
- ✦OpenAI API proxy
- ✦Model aggregation (OpenAI, Gemini, DeepSeek, Llama, Qwen, Claude, etc.)
- ✦Unified OpenAI API standard
- ✦Unlimited concurrency
- ✦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
- ✦Switch across 300+ hosted and local AI models
- ✦Native macOS app with global shortcut and screenshot-to-answer
- ✦Reusable agents, projects, and forked chats
- ✦Multimodal analysis of PDFs, images, and code
- ✦MCP tools and code execution
- ✦Local chat storage with encryptable API keys
- ✦Omni multimodal model research and development
- ✦Real-time inference API (Infer) for enterprise use
- ✦Video tagging, search, and clipping infrastructure
- ✦Training data generation from egocentric and robotics footage
Use cases
- →Deploying and scaling model inference
- →Fine-tuning and training models
- →Running batch/parallel AI jobs
- →Executing untrusted code in sandboxes
- →Integrating multiple AI models into applications using a single API
- →Accessing the latest AI models through a unified interface
- →Managing and scaling AI model usage with unlimited concurrency
- →Private local AI chat
- →Using multiple models in one app
- →Avoiding cloud data sharing
- →Experimenting with open models
- →Using multiple AI providers in one place
- →Explaining or fixing on-screen content instantly
- →Building reusable task-specific agents
- →Analyzing documents and screenshots privately
- →Powering robotics perception with multimodal AI
- →Running large-scale video search and analysis via API
- →Sourcing specialized training data for frontier AI models
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