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✓ verifiedFreemium
Open-source AI coding assistant offering autocomplete and chat in IDEs; the company was acquired by Cursor.
👁 775K/mo
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Consistent Character by fofr
✓ verifiedPaid
Pay-per-use cloud API to run, fine-tune, and deploy thousands of open-source and proprietary AI models with one line of code.
👁 1.3M/mo♥ 17K
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Replit
✓ verifiedFreemium
AI app-building platform where autonomous coding agents build, test, and deploy full-stack web and mobile apps from a prompt.
Pricing
No public pricing
No public pricing
CPU (Small): $0.000025/sec ($0.09/hr)
Nvidia A100 80GB: $0.0014/sec ($5.04/hr)
Nvidia H100: $0.001525/sec ($5.49/hr)
Free trial available
Starter: $0/month (free daily Agent credits)
Core: $20/month billed annually, $25/month billed monthly (monthly credits included)
Pro: $95/month billed annually, $100/month billed monthly (monthly credits included)
Core features
- ✦Fast tensor operations
- ✦Differentiable tensors for gradient-based optimization
- ✦Network connectivity
- ✦Integration with Bun and Flashlight
- ✦Support for GPU computation with CUDA (Linux) and CPU computation (macOS)
- ✦Open-source AI code assistant
- ✦Customizable autocomplete
- ✦In-editor AI chat
- ✦Community-built coding agent
- ✦One-line API calls to run community and proprietary AI models
- ✦Support for image, video, speech, and LLM generation models
- ✦Fine-tuning and custom model deployment via Cog
- ✦Per-second usage billing on shared or dedicated hardware
- ✦Automatic scaling for high-traffic private models
- ✦Thousands of community-published models with production APIs
- ✦Autonomous AI coding agent that builds and deploys apps end to end
- ✦Visual, code-connected design canvas for UI tweaks
- ✦Built-in database and one-click publishing/hosting
- ✦Parallel multi-agent task execution for large projects
- ✦Integrations with tools like Linear, Notion, and Excel
- ✦Convert web apps into mobile apps
- ✦Credit-based usage billing on paid tiers
Use cases
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Get AI code completions while coding
- →Ask questions about code in the editor
- →Build on an open-source coding-agent foundation
- →Developers embedding image/video/speech generation into an app via API
- →Teams deploying and scaling their own fine-tuned models
- →Builders comparing outputs from multiple AI models in one playground
- →Companies avoiding GPU infrastructure management for ML inference
- →Non-developers building working apps by describing them in prompts
- →Teams prototyping business or mobile apps quickly
- →Developers offloading repetitive coding/coordination to an AI agent
- →Enterprises needing SSO and dedicated environments for AI app building
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