Comparison

Comparison of open-weight models: Llama, DeepSeek, Qwen, and Mistral

If you want to run the AI model on your own server or computer, these four families are the most important options. Check out the differences in their license, size, Persian quality, and use cases.

"Open-weight" means the model files have been released and you can run it without the internet and without sending data to the creator company. However, licenses are not identical and the right choice depends on your hardware and use case.

CriterionLlamaDeepSeekQwenMistral
Creator Meta (USA)DeepSeek (China)Alibaba (China)Mistral AI (France)
License Meta proprietary license with conditionsOpen license (MIT for R1)Mostly Apache 2.0Partially Apache 2.0, partially commercial
Size variety ManyMostly large models + distilled versionsVery highIntermediate
Strength Ecosystem and ToolsReasoning, Math, and CodeVariety and multilingualismPerformance and speed
Persian quality (large versions) IntermediateGoodGoodIntermediate
Run on a regular laptop Small versionsDistilled versionsSmall versions (best variety)Small versions
Best for Fine-tuning and product buildingReasoning tasks and affordable APIGeneral-purpose local executionEuropean organizations and lightweight models

Summary and our recommendation

To start running locally, a small Qwen model or a distilled version of DeepSeek is usually the best balance of quality and speed. If you intend to fine-tune and build a product, the Llama ecosystem has the most educational resources. For commercial use, be sure to read the license text of the exact version you are downloading.

Step-by-step tutorial: Running Language Models on a Personal Computer with Ollama.

This comparison is based on user experience and public information from the creators up to date Oct 28, 2026 It is written as an editorial opinion, not the result of an official benchmark. Capabilities and prices change constantly.

Complete introduction of each option