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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
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Code Arena
✓ verified
Platform to compare AI coding models and generate multi-file apps side-by-side.
👁 35M/mo♥ 201
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OpenRouter
✓ verifiedFreemium
Unified API routing across many LLMs with pricing and uptime optimization.
👁 17M/mo
Pricing
No public pricing
No public pricing
No public pricing
No public pricing
No public pricing
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
- ✦MLOps and LLMOps platform
- ✦Experiment tracking and visualization
- ✦Hyperparameter optimization (Sweeps)
- ✦Model and dataset registry
- ✦Artifact versioning and management
- ✦Reporting and visualization
- ✦SDK for logging experiments and artifacts
- ✦Automated workflows
- ✦AI application debugging and evaluation
- ✦Prompt engineering tools
- ✦Unified API for multiple LLMs
- ✦Model routing visualization
- ✦Custom data policies
- ✦Price and performance optimization
- ✦Higher availability through distributed infrastructure
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
- →Train and fine-tune LLMs
- →Computer Vision
- →Time Series analysis
- →Recommender Systems
- →Classification & Regression
- →Build AI agents and applications
- →Accessing multiple LLMs through a single API
- →Implementing custom data policies for LLM usage
- →Ensuring high availability of AI models
- →Optimizing costs without sacrificing speed
- →Building AI applications with reliable and diverse models
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