Open-Source vs Closed AI: What Llama, Mistral, and DeepSeek Actually Mean

AI models split into two camps: closed (OpenAI's GPT, Anthropic's Claude, Google's Gemini — you can only access via API) and open-source (Meta's Llama, Mistral, DeepSeek, Qwen — you can download the model weights and run them yourself). Open models are usually a step behind closed in raw quality but free, private, and can be run on your own hardware (M-series Mac with 16GB+ RAM runs Llama 3 8B). The split has huge implications: control, cost, censorship, geopolitics. DeepSeek's January 2025 release rocked the industry by showing open models can match closed at a fraction of the training cost.

Some examples

• DeepSeek-V3 (Jan 2025) cost ~$5M to train and matched GPT-4o — vs OpenAI's reported $100M+ on GPT-4 — wiped $1T off Nvidia briefly.
• Run Llama 3 8B free on your Mac with LM Studio or Ollama — no internet, no logging, no quota; quality is around GPT-3.5.
• Mistral Small 3 (early 2025) is the current sweet spot for free local models on consumer laptops.
• Open models can be uncensored (no safety guardrails) — both a feature for serious research and a risk for misuse, hence the policy debate.

Try it!

Download Ollama (free, ollama.com) and run Llama 3 8B on your laptop tonight. No account, no internet needed, fully private. Ask it anything. You just ran AI you OWN.