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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
Pricing
No public pricing
No public pricing
No public pricing
Open Source: $0
Enterprise: Contact for Pricing
No public pricing
Free trial available
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
- ✦LLM Gateway for 100+ LLMs
- ✦OpenAI-compatible API
- ✦Cost Tracking and Budget Management
- ✦LLM Fallbacks
- ✦Load Balancing
- ✦Rate Limiting
- ✦Prompt Management
- ✦Logging and Error Tracking
- ✦Enhanced Context Engineering for deep codebase analysis and adaptive memory
- ✦Intelligent Agents for autonomous planning, coding, and testing
- ✦Spec-Driven Development for clarifying requirements and automating execution
- ✦Intelligent Codebase Search and Advanced Repository Insight
- ✦Context-aware code completions and next-edit suggestions
- ✦Support for leading AI models (Claude, GPT, Gemini)
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
- →Giving developers access to multiple LLMs
- →Managing spend across different LLM providers
- →Implementing LLM fallbacks for reliability
- →Standardizing LLM API access across an organization
- →Delegating complex software development tasks to AI agents for autonomous completion.
- →Performing multi-file code edits and refactoring through natural language chat.
- →Gaining deep architectural understanding of a codebase to resolve issues with precision.
- →Generating unit tests, code explanations, and uncovering codebase architecture.
- →Systematically tackling software development tasks from planning to testing.
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