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Qoder
✓ verifiedFreemium
Agentic AI platform with a coding desktop app, CLI, and cloud agents for autonomous software development and office work.
👁 2.7M/mo♥ 32K
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ApX Machine Learning
✓ verifiedFreemium
Tools, model specs and courses for LLM engineers-VRAM calculator, benchmarks and model directory-with free and paid tiers.
👁 355K/mo
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Anima
✓ verifiedFreemium
AI design-to-code tool that converts Figma designs or cloned websites into HTML/React and builds apps with vibe coding.
👁 321K/mo♥ 1.3K
Pricing
No public pricing
No public pricing
Free trial available
Basic: $0/mo (free forever)
Pro: $19/mo
Pro+: $59/mo
Free: $0/mo (5 code generations/day, 5 imports)
Enterprise: from $500/mo billed annually (SSO, SLAs)
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)
- ✦Multi-agent collaboration for end-to-end tasks
- ✦Persistent memory and custom rules
- ✦Extensible skills and plugins
- ✦Rich context across code, images, and directories
- ✦Automatic codebase documentation generation
- ✦Terminal-native CLI and JetBrains IDE plugin
- ✦Cloud-hosted agents for enterprise use
- ✦VRAM/GPU-memory calculator for LLMs
- ✦LLM performance rankings and benchmarks
- ✦Model directory and comparison
- ✦AI/ML courses and learning roadmap
- ✦Calculator API and exportable cost reports
- ✦Engineering blog and guides
- ✦Figma-to-code (HTML/React)
- ✦Clone any or private website to code
- ✦AI website and app builder
- ✦Figma agent (Buddy) and design agent
- ✦Anima MCP server and API
- ✦Adobe XD support
Use cases
- →Creating and manipulating datasets
- →Training small machine learning models
- →Implementing advanced training and inference logic
- →Building applications that require tensor computations
- →Autonomous feature development in large codebases
- →Terminal-based AI pair programming
- →Cross-department task automation for legal, finance, HR
- →Onboarding developers to unfamiliar codebases
- →Estimating GPU memory before training or inference
- →Comparing and selecting LLMs
- →Learning ML and LLM engineering
- →Modeling production deployment costs
- →Converting Figma designs to code
- →Cloning sites as starting points
- →Building web apps with AI
- →Automating design-to-code in dev workflows
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