ChatGPT vs Claude vs Gemini
3-way comparison of the top AI assistants
The Big Three: How Do They Compare?
ChatGPT (OpenAI), Claude (Anthropic), and Gemini (Google) are the three most widely used AI assistants in 2026. Each is built on different training data, architectures, and design philosophies — yet when asked factual questions, they often converge on the same answers.
This page shows pairwise agreement data for all three combinations. When two models independently produce the same factual claims, it's a strong reliability signal. When all three agree, you can be even more confident. Disagreements highlight areas where you should verify information independently.
The data below is generated from questions analyzed by NoParrot. It reflects how these models actually perform on the kinds of questions people ask every day.
Pairwise Agreement
| Model Pair | Agreement | Questions analyzed |
|---|---|---|
| ChatGPT vs Claude | 76.8% | 240 |
| ChatGPT vs Gemini | 81.4% | 237 |
| Claude vs Gemini | 78.9% | 238 |
Which Model Agrees Most With Others?
Average pairwise agreement — a higher score means the model's answers are more consistent with the other two.
ChatGPT vs Claude — By Category
| Category | Agreement | Stronger model |
|---|---|---|
| medical | 87.5% | ChatGPT |
| other | 86.3% | Claude |
| science | 16.1% | Claude |
| general_knowledge | 0% | ChatGPT |
ChatGPT vs Gemini — By Category
| Category | Agreement | Stronger model |
|---|---|---|
| other | 94% | Gemini |
| medical | 85.7% | ChatGPT |
| science | 19.4% | Gemini |
| general_knowledge | 0% | ChatGPT |
Claude vs Gemini — By Category
| Category | Agreement | Stronger model |
|---|---|---|
| other | 94.3% | Claude |
| medical | 81.2% | — |
| general_knowledge | 57.1% | Gemini |
| science | 24.5% | Gemini |
Methodology
NoParrot sends the same question to ChatGPT, Claude, and Gemini simultaneously. Each response is broken into individual factual claims, which are then compared pairwise using embedding-based semantic matching. Agreement percentages reflect how often two models independently produce the same factual claims. Contradictions are detected through targeted LLM analysis of semantically similar but potentially conflicting claims.
Try this comparison yourself
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