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Gemini 1.0 Pro vs o4-mini
Comprehensive side-by-side LLM comparison
o4-mini leads with 24.8% higher average benchmark score. o4-mini offers 259.0K more tokens in context window than Gemini 1.0 Pro. Gemini 1.0 Pro is $3.50 cheaper per million tokens. o4-mini supports multimodal inputs. Overall, o4-mini is the stronger choice for coding tasks.
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Gemini 1.0 Pro is a language model developed by Google. The model shows competitive results across 9 benchmarks. Notable strengths include BIG-Bench (75.0%), MMLU (71.8%), WMT23 (71.7%). The model is available through 1 API provider. Released in 2024, it represents Google's latest advancement in AI technology.
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OpenAI
o4-mini is a multimodal language model developed by OpenAI. It achieves strong performance with an average score of 66.5% across 14 benchmarks. It excels particularly in AIME 2024 (93.4%), AIME 2025 (92.7%), MathVista (84.3%). It supports a 300K token context window for handling large documents. The model is available through 1 API provider. 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.
1 year newer
Gemini 1.0 Pro
2024-02-15
o4-mini
OpenAI
2025-04-16
Pricing Comparison
Cost per million tokens (USD)
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Gemini 1.0 Pro
Input:$0.50
Output:$1.50($3.50 cheaper)
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o4-mini
Input:$1.10
Output:$4.40
Performance Metrics
Context window and performance specifications
Average performance across 20 common benchmarks
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Gemini 1.0 Pro
Average Score:21.8%
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o4-mini
Average Score:46.5%(+24.8%)
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Knowledge Cutoff
Training data recency comparison
Gemini 1.0 Pro
2024-02-01
o4-mini
2024-05-31
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 1.0 Pro
1 providers
Throughput: 120 tok/s
Latency: 0.4ms
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o4-mini
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Gemini 1.0 Pro
Avg Score:21.8%
Providers:1
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o4-mini
Avg Score:46.5%(+24.8%)
Providers:1