GMAT Focus_ Material & Practice

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With a 740 GMAT score, rich business consulting experience and plenty of community service, Kumar Ayush knew he had a strong profile for the top MBA programs. In his first year of applications, he applied to a few top colleges on his own, but wasn’t able to convert them. While most strong candidates keep wondering about what went wrong, Ayush was lucky to get some helpful feedback from one of the official MBA admission teams. They said that despite his accomplishments, there was one key issue that was working against him. And that’s what he focused on in his second year of applications, which resulted in interview calls from every program he applied to.

Here's how the top 6 stack up in 2026: (See the sheet for more details and updates 👇) 1. Claude Opus 4.5 The model I rely on most. Best for: Strong reasoning and long-form thinking Handles complex documents without losing structure Downside: Less spontaneous with creative ideas New updates:  Claude Code, Cowork, and Excel will change how technical teams work.  2. ChatGPT-5.2 Still the most versatile tool available. Best for: Strong reasoning and multimodal support. Fast for content, workflows, and experimentation Downside: Costs increase quickly with heavy usage New updates:  With Health features, Atlas, and Apps, ChatGPT has captured more of the market.  3. Gemini 3 Google’s model, now properly usable. Best for: Multimodal understanding across documents and data Very good for research-heavy work inside Google-heavy teams.  Downside: Creative output can feel restrained New updates:  Nano Banana with revolutionary image creation, Gemini 3, and personal intelligence. 4. Perplexity The fastest way to get reliable answers. Best for: Real-time search with clear citations Transparent sources reduce guesswork  Downside: Limited creative generation New updates:  Learn Mode for structured, guided understanding and a new AI browser, Comet. 5. Grok 4.1 Strong awareness of what’s happening now. Best for: Real-time trend and cultural context Useful for social listening and narratives Downside: Limited use for structured or technical work New updates:  The new image generation feature is impressive (if not controversial !).  6. DeepSeek 3.2 Open-source, highly efficient for technical teams. Best for: Strong quantitative and STEM reasoning High performance relative to cost Downside: Limited documentation outside Asia New updates:  3.2, which is essentially DeepSeek 3.1 with better reasoning and stability. Each model will serve a slightly different purpose. I encourage everyone to test them and make up their own mind. The more you experiment, the more value each one can provide.  Which LLMs are you already using? Which ones are you most curious about?