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Side-by-side features, use cases and pricing — because the right pick depends on your job and budget, not just the ranking.
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DeepSeek V4
✓ verifiedFree
DeepSeek's official domain and foundation-model line; major AI lab.
👁 430M/mo
✕
Code Arena
✓ verified
Platform to compare AI coding models and generate multi-file apps side-by-side.
👁 35M/mo♥ 201
✕
Runpod
✓ verifiedPaid
Cost-effective GPU rentals and serverless inference for AI; heavy adoption.
👁 2.3M/mo
Pricing
No public pricing
No public pricing
No public pricing
MI300X: Starting from $2.49/hr
H100 PCIe: Starting from $1.99/hr
A100 PCIe: Starting from $1.19/hr
A100 SXM: Starting from $1.89/hr
A40: Starting from $0.4/hr
L40: Starting from $0.69/hr
L40S: Starting from $0.79/hr
RTX A6000: Starting from $0.33/hr
RTX A5000: Starting from $0.16/hr
RTX 4090: Starting from $0.34/hr
RTX 3090: Starting from $0.22/hr
RTX A4000 Ada: Starting from $0.20/hr
Network Storage: $0.05/GB/month
Core features
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- ✦General large language models (LLM)
- ✦Code generation models
- ✦Mixture of Experts (MoE) models
- ✦API access to models
- ✦Context Caching
- ✦Side-by-side AI model comparison
- ✦Multi-file app and website generation
- ✦Export to GitHub or IDE
- ✦Image to Code (screenshot to code conversion)
- ✦Real-time code quality and reasoning evaluation
- ✦AI coding model leaderboard
- ✦GPU Cloud for on-demand GPU rentals
- ✦Serverless GPU for scalable ML inference
- ✦Support for PyTorch, TensorFlow, and other AI frameworks
- ✦Custom container deployment
- ✦Network storage
- ✦CLI tool for hot reloading and deployment
Use cases
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- →Chatbots and conversational AI
- →Code completion and generation
- →Reasoning and problem-solving
- →Text generation and summarization
- →Mathematical problem solving
- →Search
- →Writing
- →Reading
- →Comparing the logic and reasoning of different AI models for a specific coding task
- →Generating a complete multi-file website structure from a single prompt
- →Converting a UI mockup image into functional frontend code
- →Benchmarking the performance of new AI coding models
- →Developing and training AI models
- →Scaling ML inference for applications
- →Deploying AI applications in minutes
- →Running machine learning training tasks
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