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Gemini 2.0 Flash Thinking vs GPT-5 nano
Comprehensive side-by-side LLM comparison
GPT-5 nano leads with 3.9% higher average benchmark score. GPT-5 nano is available on 2 providers. Both models have their strengths depending on your specific coding needs.
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Gemini 2.0 Flash Thinking is a multimodal language model developed by Google. It achieves strong performance with an average score of 74.3% across 3 benchmarks. Notable strengths include MMMU (75.4%), GPQA (74.2%), AIME 2024 (73.3%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Google's latest advancement in AI technology.
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OpenAI
GPT-5 nano is a multimodal language model developed by OpenAI. The model shows competitive results across 5 benchmarks. It excels particularly in AIME 2025 (85.2%), HMMT 2025 (75.6%), GPQA (71.2%). It supports a 528K token context window for handling large documents. The model is available through 2 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents OpenAI's latest advancement in AI technology.
6 months newer
Gemini 2.0 Flash Thinking
2025-01-21
GPT-5 nano
OpenAI
2025-08-07
Performance Metrics
Context window and performance specifications
Average performance across 7 common benchmarks
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Gemini 2.0 Flash Thinking
Average Score:31.8%
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GPT-5 nano
Average Score:35.8%(+3.9%)
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Knowledge Cutoff
Training data recency comparison
GPT-5 nano
2024-05-30
Gemini 2.0 Flash Thinking
2024-08-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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Gemini 2.0 Flash Thinking
0 providers
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GPT-5 nano
2 providers
OpenAI
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Gemini 2.0 Flash Thinking
Avg Score:31.8%
Providers:0
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GPT-5 nano
Avg Score:35.8%(+3.9%)
Providers:2