Hi everyone! Early 2026 again brings talk of DeepSeek and similar high-performing "more open" models. Even if you only use ChatGPT or Claude, it's worth watching – it pushes prices down, speeds innovation, and changes how we think about chat AI. This isn't "everyone must run GPT at home" propaganda – it's an honest look at who gains what.

🔹 What's the point of open / semi-open models?
More models run locally (PC, server), cheaply via API, or under open / partial licenses. Weights, architecture details, fine-tuning – much leaves the big closed box. Big players (OpenAI, Anthropic, Google) must compete – good for you: better free tiers, cheaper API, faster progress.

The DeepSeek line stood out because it looks strong on benchmarks and everyday tasks – not just a "cheap copy."

🔹 Pros and cons
🔹 Pros: cheaper use, data can stay with you (local run), customizable (fine-tune, own RAG), great for experiments.
🔹 Cons: setup, maintenance, hardware needs, weaker security if misconfigured; fewer ready-made integrations than the ChatGPT app.

✅ Worth open models if: you're a developer, privacy matters, you optimize cost, or you want to learn how models work.
❌ Stay on cloud if: you only want easy chat, no time for DevOps, and you need latest multimodal features now.

🔹 Beginner vs advanced – my advice
For beginners, cloud chat (ChatGPT, Claude, Gemini) stays easiest – see AI tips for 2026. Advanced users should try a local or open model at least once (Ollama, LM Studio, API providers) – you learn how the system "thinks" and why prompt and context matter.

🔹 Impact on the "big three"
Chat AI isn't just three names – and in 2026 that's increasingly true. Closed models stay strong on integrations, multimodal, support. The open wave pressures price and speed. My 2025 review covered this competition – early 2026 continues it.

🔹 Security and responsibility
Local isn't automatically "safer" – a badly exposed server is still risk. For company data, check license, logging, access. Don't upload secrets to APIs you don't trust.

🔹 How to start – concrete steps for advanced users
No server farm required day one. Start: Ollama or LM Studio on your machine, a smaller open model (Llama, Mistral, local DeepSeek variant – depends what runs for you). Download, launch, ask what you'd ask ChatGPT – watch differences in speed, quality, tone.

Step two: API provider (DeepSeek API, Together, Groq, etc.) – can be cheaper at volume, but data leaves your machine. Read the terms. The how chat AI works piece helps explain tokens and context behind the scenes.

🔹 RAG and fine-tune – when they're worth it
RAG (Retrieval Augmented Generation): add your documents via search – company knowledge base, your posts, technical docs. Advanced but not rocket science. Fine-tune: tune the model on your data – pricier, slower, more for company projects.

Neither is mandatory for beginners. If you only chat, cloud ChatGPT/Claude is enough. If you're a dev and don't want client data scattered: RAG locally or in a closed environment can help. The agents post connects too: many "custom AIs" are open model + RAG + tools.

🔹 DeepSeek vs ChatGPT daily – honest picture
DeepSeek via API or app is strong on everyday tasks – summaries, code scaffolds, translation. It doesn't beat the latest GPT or Opus at everything, but price/value makes it a second line for many. The GPT vs Claude debate plays at premium tier; the open wave pressures lower and mid segments.

Gaboo strategy: one main cloud tool (what you know) + open model experiments when you have time to learn. No need to replace everything – just know choice exists, and competition made big players better in 2025–2026.

🌍 Summary
DeepSeek and the open wave won't replace ChatGPT for everyone – but they reshape the market. Use it consciously: cloud for convenience, open models for control and learning. Best strategy for many: one main cloud tool + open experiments when you have time.

Further information and sources used: