
Evaluation criteria
I don't just look at 'smartness'. I judge assistants by reasoning quality, code fidelity, ecosystem integrations, and governance features. Latency and context window size also matter immensely for longer architecture explorations.
The 'vibe' of the model matters too. Some models are terse and robotic (good for scripts), while others are verbose and explanatory (good for learning). Choosing the right personality for the task reduces friction.
Where each model excels
ChatGPT (GPT-4o) is my versatile 'Swiss Army Knife'. It has the best UI, the widest plugin ecosystem, and great voice mode. It's my default for quick queries, creative ideation, and front-of-house copy.
Claude 3 Opus (and Sonnet) wins hands-down on long-form reasoning and coding. Its large context window allows me to paste entire documentation pages or complex file structures, and it follows instructions with much higher fidelity. It feels more 'human' and less prone to lazy answers.
Gemini Advanced is the specialist. I slot it in when I need deep integration with Google Workspace data or real-time search. Its ability to pull from my emails or Drive documents makes it a powerful personal assistant.
- ChatGPT: best UI polish, tool use, and fast iteration
- Claude: strongest choice for coding, complex reasoning, and writing
- Gemini: native tie-ins to Google ecosystem and multimodal inputs
The Blended Workflow
In practice, I don't choose one; I route tasks. I might use Claude to draft a detailed decision log because of its Nuance. Then I'll feed that text into ChatGPT to generate 10 UI variations because of its creativity. Finally, I'll use Gemini to check those variations against current market trends via Google Search.
This 'Model Routing' strategy ensures I'm always using the sharpest tool for the specific job at hand.
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