The LLM landscape is moving fast and choosing the right model in 2026 is becoming a real technical and business challenge.
Between GPT, Claude, LLaMA, Mistral, and a growing list of open and closed models, the decision is no longer about which one is the best overall, but which one actually fits your use case, constraints, and budget.
At ClickIT, we usually share our insights through video content, but we know many developers and tech leaders prefer discovering ideas through platforms like dev.to. That’s why we wanted to share this recent breakdown from one of our AI Engineers:
🎥 LLMs in 2026: Trends, Tools, & How to Choose the Right One
In this video, we go beyond model hype and focus on practical evaluation. It covers:
- What actually matters when working with LLMs in 2026
- Key trends shaping how models are built and adopted
- How to evaluate an LLM based on cost, performance, and scalability
- Which models are standing out and why
- What to expect next as enterprise AI adoption grows
Whether you’re experimenting with AI internally or planning a production-grade AI project, understanding how to select (or combine) LLMs is becoming a core engineering skill.
If you’re interested in building an AI stack that’s secure, scalable, and aligned with real business outcomes, our AI engineers at ClickIT work on everything from single-model setups to hybrid, multi-model architectures.
We’ll keep sharing practical AI insights across platforms, hope this one adds value to your current or future projects.
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