Compare tools
Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.
⇄ Comparison dimension — pick the market you're actually shopping in
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DesignCode UI
✓ verifiedPaid
Premium Figma and Framer UI kit with hundreds of components, variants and icons for building polished, themeable sites.
5.0K visits/mo
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Runware
✓ verifiedFreemium
Pay-as-you-go API aggregating thousands of image, video, audio and LLM models with custom inference hardware for lower per-request cost.
249K visits/mo
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AnythingLLM
✓ verifiedFree
Free all-in-one desktop AI app to chat with your documents and run RAG and AI agents fully local and private.
682K visits/mo
Pricing
All-Access: $49 one-time (300+ components)
Pro: $120/year
vCPU compute: $0.016/hr
RTX PRO 6000: $1.99/hr (as low as $0.99)
H100: $2.76/hr
H200: $3.18/hr
B200: $4.99/hr
Free trial available
No public pricing
Core features
- ✦300+ Figma UI components
- ✦2,000+ Figma variants
- ✦2,116 icons
- ✦Framer-ready components and templates
- ✦Deep theming (glass, line, flat styles)
- ✦Adaptive layouts with variables
- ✦Single API for image, video, audio, 3D and LLM models
- ✦Standardized model addressing across hosted, partner and custom uploads
- ✦Support for LoRAs, ControlNets, VAEs and embeddings on open-source models
- ✦WebSocket and REST access with async webhook delivery
- ✦Pay-per-request billing with no infrastructure to manage
- ✦Raw serverless GPU/CPU compute for custom workloads
- ✦Chat with your documents (RAG)
- ✦Runs locally and offline for privacy
- ✦Supports any LLM (local or cloud)
- ✦Built-in AI agents
- ✦Handles PDFs, Word, CSV, codebases
- ✦No-code setup
Use cases
- →Build a website or app UI in Figma
- →Hand off Figma designs to Framer
- →Speed up prototyping with prebuilt components
- →Adding AI image or video generation to an app without managing infra
- →Batching multi-modal generation tasks in one API call
- →Running custom fine-tuned models via Model Upload
- →Cutting inference costs at high generation volume
- →Privately querying your own documents
- →Running local AI without the cloud
- →Building AI agents over your data
- →Using multiple LLM providers in one app
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