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DeepSeek-V3.2-Exp vs Gemini 1.0 Pro
Comprehensive side-by-side LLM comparison
DeepSeek-V3.2-Exp leads with 22.3% higher average benchmark score. DeepSeek-V3.2-Exp offers 188.4K more tokens in context window than Gemini 1.0 Pro. DeepSeek-V3.2-Exp is $1.32 cheaper per million tokens. Overall, DeepSeek-V3.2-Exp is the stronger choice for coding tasks.
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DeepSeek
DeepSeek-V3.2-Exp is a language model developed by DeepSeek. It achieves strong performance with an average score of 66.1% across 14 benchmarks. It excels particularly in SimpleQA (97.1%), AIME 2025 (89.3%), MMLU-Pro (85.0%). It supports a 229K token context window for handling large documents. The model is available through 2 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents DeepSeek's latest advancement in AI technology.
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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.
1 year newer
Gemini 1.0 Pro
2024-02-15
DeepSeek-V3.2-Exp
DeepSeek
2025-09-29
Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V3.2-Exp
Input:$0.27
Output:$0.41($1.32 cheaper)
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Gemini 1.0 Pro
Input:$0.50
Output:$1.50
Performance Metrics
Context window and performance specifications
Average performance across 22 common benchmarks
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DeepSeek-V3.2-Exp
Average Score:42.1%(+22.3%)
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Gemini 1.0 Pro
Average Score:19.8%
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Knowledge Cutoff
Training data recency comparison
Gemini 1.0 Pro
2024-02-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek-V3.2-Exp
2 providers
Novita
ZeroEval
Throughput: 100 tok/s
Latency: 0.7ms
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Gemini 1.0 Pro
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DeepSeek-V3.2-Exp
Avg Score:42.1%(+22.3%)
Providers:2
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Gemini 1.0 Pro
Avg Score:19.8%
Providers:1