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Explore Open Source AI
What is Open Source AI?
Complete guide to open source AI: definition, benefits, top models, and how to get started with free LLMs.
Read the guide →Best Open Source AI Models 2025
Top 100 free LLMs ranked by performance, cost, and use case. Compare LLaMA, Mixtral, Qwen, and more.
View rankings →Why Choose The Open Source AI?
Everything you need to discover, evaluate, and deploy open-source AI models
ONE API
Access 100+ open-source models through a single, unified API for seamless integration.
117+ Evaluations
Comprehensive testing across safety, quality, compliance, and advanced capabilities.
KYI™ Benchmarking
7-pillar scoring system for holistic model assessment beyond just accuracy.
Community-Driven
Reviews, ratings, and user-submitted benchmarks from AI practitioners worldwide.
How It Works
Three simple steps to AI excellence
Discover
Search 100+ open-source models with semantic search and smart filtering
Evaluate
Run 117+ tests or create custom evaluations to find the RIGHT model
Build
Deploy with ONE API - OpenAI-compatible, transparent pricing, 99.9% uptime
Popular Comparisons
View all modelsLLaMA 3.1 405B vs GPT-4
Compare the largest open source model against OpenAI's flagship
Mixtral 8x22B vs Claude 3 Opus
Efficient mixture of experts vs Anthropic's most capable model
Qwen 2.5 72B vs Gemini Pro
Multilingual powerhouse vs Google's production model
Stable Diffusion 3 vs DALL-E 3
Open source image generation vs OpenAI's creative AI
Whisper Large v3 vs Google Speech API
OpenAI's speech recognition vs Google's cloud service
CodeLlama 70B vs GitHub Copilot
Open source code generation vs Microsoft's AI pair programmer
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Frequently Asked Questions
What are open source AI models?
Open source AI models are machine learning models whose source code, architecture, and weights are publicly available. They can be freely used, modified, and deployed without vendor lock-in, offering transparency and cost savings compared to proprietary alternatives.
How do I choose the best open source AI model for my project?
Consider your specific use case, required performance metrics, available compute resources, and licensing requirements. Our KYI benchmarking system evaluates models across speed, quality, and cost to help you make informed decisions. Start by browsing models in your category of interest.
Are open source AI models as good as proprietary ones like GPT-4?
Many open source models like LLaMA 3.1, Mixtral, and Qwen 2.5 now match or exceed proprietary models in specific tasks. While GPT-4 excels in general reasoning, open source alternatives offer comparable performance with benefits like data privacy, customization, and no usage limits.
Can I use open source AI models commercially?
Yes, most open source AI models can be used commercially, but always check the specific license. Popular licenses include Apache 2.0, MIT, and custom licenses like LLaMA's community license. Our model pages clearly display licensing information for each model.
How much does it cost to run open source AI models?
Costs vary based on model size and infrastructure. Small models (7B parameters) can run on consumer GPUs, while large models (70B+) require enterprise hardware. Cloud hosting typically costs $0.50-$5 per million tokens. Self-hosting eliminates per-token costs but requires upfront hardware investment.