If you're new to Ollama, we recommend starting with these two articles before choosing your first model.

 

Once Ollama is installed, the next question is almost always the same.

Which model should you download first?

Open the Ollama library and you'll immediately see names like Qwen, Llama, Gemma, DeepSeek and Mistral. For someone just getting started, the number of choices can be confusing.

The good news is that there isn't a single "best" model. Each one has its own strengths, and the right choice depends on what you're trying to accomplish. Ollama makes it easy to switch between models, so you're not locked into one option.

For SEO professionals, we generally recommend starting with Qwen.

It has quickly become one of the most interesting open models for writing, summarising information and following detailed instructions. It performs well across many everyday tasks, making it a solid first choice if your work involves research, drafting ideas or analysing documentation.

Llama is another excellent option.

As one of the best-known open models, it's supported by a large community and works well for general conversations, brainstorming and experimentation. If you're curious about local AI but don't yet have a specific workflow in mind, Llama remains a safe place to start.

Gemma is worth considering if you prefer a lighter model that can run comfortably on more modest hardware. While it may not match larger models on every task, it often provides a good balance between speed and capability.

DeepSeek has attracted attention for coding and technical reasoning. Developers frequently use it for programming-related tasks, but it can also be useful when working through structured technical problems.

Mistral continues to be a reliable all-round performer. It's fast, efficient and still a favourite among many people experimenting with local AI.

One mistake beginners often make is downloading the largest model they can find.

Bigger doesn't automatically mean better.

A model that runs smoothly on your computer will usually provide a much better experience than a larger one that responds slowly or struggles because of hardware limitations. Choosing a model that fits your machine is often more important than choosing the one with the highest benchmark scores.

Another important point is that you don't have to choose just one model.

One of Ollama's biggest advantages is how easy it is to experiment. You can download several models, compare their responses and decide which one fits your own workflow. Many experienced users end up using different models for different tasks rather than relying on a single assistant. Community discussions increasingly focus on building practical workflows around local models instead of searching for one perfect model.

This is exactly what we'll be doing in AI Labs.

Rather than relying on benchmarks alone, we'll test Qwen, Llama, Gemma, DeepSeek and other models in real SEO scenarios. We'll compare how they handle research, content planning, prompt engineering and everyday publishing tasks to understand where each model performs best.

Because choosing your first model isn't really the finish line.

It's the beginning of discovering which local AI assistant works best for the way you actually work.