- Llama 3.1 (Meta) — Best All-Round Model
- Mistral (7B) — Fastest Model for Everyday Use
- Gemma 2 (Google)
- DeepSeek / Phi 3
- Qwen (Alibaba)
- LLaVA / Vision Models
- Comparison Table — Choose the Right Model Easily
- Which Model Should YOU Use?
- List all models present on your machine
- FAQ
- Conclusion
- References
After installing Ollama and running your first model, the next question is obvious
Which AI model should I use?
Ollama supports many popular open source models like Llama 3, Mistral, Gemma, Phi, Qwen, and even vision models.
But every model behaves differently some are better at coding, some are good for writing, some are extremely fast, and some need more system resources.
In this guide, I’ll explain the best Ollama models, what they’re good at, how heavy they are, and which one You should choose depending on your use case.
Let’s make this simple and practical.
Llama 3.1 (Meta) — Best All-Round Model
Recommended for General chat, writing, learning, everyday use
Why it’s good
- Balanced performance
- Great at reasoning
- Good at long-form answers
- Strong English performance
Runs well on most laptops (7B/8B versions)
You can run Llama 3.1 model using below command
ollama pull llama3.1
ollama run llama3.1Best for
- Explanations
- Writing articles
- Brainstorming
- Everyday chat
- Summaries
Mistral (7B) — Fastest Model for Everyday Use
Recommended for Speed, quick replies, lightweight systems
Why it’s good
- Very fast
- Low memory usage
- Great for MacBook Air or older laptops
- Small size but surprisingly powerful
You can run Mistral (7B) model using below command
ollama pull mistral
ollama run mistralBest for
- Quick chats
- Productivity tasks
- Short answers
- Running multiple models
Gemma 2 (Google)
Recommended for Simple explanations, study help, structured writing
Why it’s good
- Clean, simple, very human like writing
- Great for students
- Easy to understand outputs
- Lightweight
you can run Gemma using below command
ollama pull gemma2
ollama run gemma2
Best for
- Notes
- Summaries
- School or college explanations
- Short articles
DeepSeek / Phi 3
Recommended for Coding, debugging, small-system usage
Why it’s good
- Extremely small (3B or 4B)
- Amazing coding performance for its size
- Very fast inference
- Great beginner coding assistant
you can run phi using below command
ollama pull phi3
ollama run phi3
Best for
- Python help
- Small code generation
- Explaining bugs
- Quick coding suggestions
Qwen (Alibaba)
Recommended for Indian languages, multilingual tasks
Why it’s good
- Strong performance in Hindi, Tamil, Bangla, Telugu, etc.
- Great for translation
- Good writing quality
- Competitive with bigger models
you can run quen using below command
ollama pull qwen2
ollama run qwen2
Best for
- Translating
- Multilingual writing
- Chatting in regional languages
LLaVA / Vision Models
Recommended for Image-to-text tasks
What they can do
- Describe images
- Extract text
- Analyze documents visually
- Identify objects
you can run the llava using below command
ollama pull llava
ollama run llava
Best for
- Captioning
- Photo description
- OCR-style tasks
Comparison Table — Choose the Right Model Easily
| Model | Best For | Speed | Hardware Need | Writing Quality | Coding Quality |
|---|---|---|---|---|---|
| Llama 3.1 | All-round tasks | Medium | Medium | ⭐⭐⭐⭐ | ⭐⭐⭐ |
| Mistral | Speed | ⭐⭐⭐⭐⭐ | Low | ⭐⭐⭐ | ⭐⭐⭐ |
| Gemma 2 | Learning, writing | ⭐⭐⭐ | Low | ⭐⭐⭐⭐ | ⭐⭐ |
| Phi 3 / DeepSeek | Coding | ⭐⭐⭐⭐⭐ | Very Low | ⭐⭐ | ⭐⭐⭐⭐ |
| Qwen 2 | Multilingual | ⭐⭐⭐ | Medium | ⭐⭐⭐⭐⭐ (multi-lang) | ⭐⭐⭐ |
| LLaVA | Vision tasks | Slow | Higher | – | – |
Which Model Should YOU Use?
If you want one model for everything → Llama 3.1
If you want maximum speed → Mistral
If you want best writing style → Gemma 2
If you want coding help → Phi 3 / DeepSeek
If you want Hindi/regional language support → Qwen 2
If you want image understanding → LLaVA
List all models present on your machine
ollama list
This will show you:
- All installed models
- Their sizes
- Their versions
FAQ
Q: Do larger models give better answers?
Mostly yes, but they need more memory.
Q: Can I run multiple models?
Yes, but one at a time unless you have a strong machine.
Q: Should beginners use 70B models?
No. They’re too heavy for normal laptops.
Conclusion
Choosing the right AI model in Ollama depends on what you want to do — write, learn, code, translate, or run AI offline quickly.
Start with Llama or Mistral, then experiment with smaller or more specialized models.
Raj Ranjan