Hey there! Choosing the right AI model in 2025 can feel like picking the perfect tool from a crowded toolbox. Even when you’re writing a blog, coding an app, researching for a project, or diving into social media trends, each AI model has its own pros and cons.

We have done a deep dive into the top players—OpenAI’s GPT models, Anthropic’s Claude, Google’s Gemini, Perplexity, Meta AI’s Llama, DeepSeek, and xAI’s Grok—to help you find the best fit for your needs.

Let’s check it out!

Models’ Capabilities

Here’s a snapshot of the top AI models to help you compare at a glance. ✅ means the feature is supported, 👍 means it’s the best in that category, and ❌ means it’s not supported. I’ve also included API pricing and key limits.

$0.0004-$0.04/1K output tokens | $0.00025 – $0.015/ 1K input tokens

$0.00125 – $0.075/ 1K output tokens | Free tier available with limited requests.

$0.000075- $0.00015/1K input tokens

$0.0003 - $0.0006/1K output tokens | $0.001-$0.003/1K input tokens

$0.001-$0.015/1K output tokens | Free tier available with limited requests.

$0.0006-$0.003/1K input tokens

$0.0005-$0.025/1K output tokens | Free to use. | $0.00014-$0.000055/1K input tokens

$0.00028-$0.00219/1K output tokens | | Everyday Answers | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | Writing | ✅ | 👍 | ✅ | ❌ | ✅ | ✅ | ❌ | | Coding | ✅ | 👍 | ✅ | ❌ | ✅ | ✅ | ✅ | | Math | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | Reasoning | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | | Web Search | ✅ | ✅ | ✅ | 👍 | ✅ | ❌ | ✅ | | Deep Research | ✅ | ❌ | ✅ | ✅ | ✅ | ❌ | ✅ | | Native Image Generation | ✅ | ❌ | ✅ | ❌ | ✅ | ✅ | ❌ | | Video Analysis | ❌ | ❌ | ✅ | ❌ | ❌ | ❌ | ❌ | | Computer Use | ✅ | ✅ | ❌ | ❌ | ❌ | ❌ | ❌ |

Deep Dive: Which AI Should You Use?

1. GPT Models (OpenAI)

Rate: 8.5/10

Best for: General-purpose use, content creation, conversational interfaces, productivity.

OpenAI’s GPT family is still the most widely deployed and user-friendly line of models. GPT-4.5 (o3) delivers smooth, emotionally intelligent conversations and excels in content-heavy workflows.

However, it's not the top performer when it comes to serious coding tasks—often trailing behind Claude in code correctness, explanation clarity, and multi-step logic.

Pros:

• Natural, fluent writing and tone.
• Excellent for summarizing, brainstorming, and communication tasks.
• Some models have higher context limit (GPT-4.1 with 1M context), appropriate to process long documents or conversations.

Cons:

• Mediocre at complex coding, debugging, or multi-step logic.
• Prone to hallucinations in technical domains.