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DeepSeek-V3.2 Thinking vs MiMo-V2-Flash
Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-V3.2-Exp (DeepSeek-V3.2 Thinking), released by DeepSeek in September 2025, is the experimental preview release of the DeepSeek-V3.2 model featuring 685 billion total parameters and integrated thinking capabilities. It introduced the architecture and training approaches that became the foundation of the final V3.2 release, including thinking in tool-use and hybrid reasoning modes.
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Xiaomi
MiMo-V2-Flash, released by Xiaomi on December 16, 2025, is a Mixture-of-Experts large language model with 309 billion total parameters and 15 billion active parameters per inference, designed for high-speed reasoning and agentic workflows. It features a 256K token context window, processes up to 150 tokens per second, and was trained on 27 trillion tokens. MiMo-V2-Flash targets open-source deployments requiring fast, capable coding and reasoning with an efficient inference footprint, under an MIT license.
2 months newer
DeepSeek-V3.2 Thinking
DeepSeek
2025-09-29
MiMo-V2-Flash
Xiaomi
2025-12-16
Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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DeepSeek-V3.2 Thinking
Average Score:73.1%
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MiMo-V2-Flash
Average Score:73.4%(+0.3%)
Performance comparison across key benchmark categories
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DeepSeek-V3.2 Thinking
Coding73.1%
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MiMo-V2-Flash
Coding73.4%(+0.3%)
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek-V3.2 Thinking
1 providers
DeepSeek
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MiMo-V2-Flash
0 providers
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DeepSeek-V3.2 Thinking
Avg Score:73.1%
Providers:1
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MiMo-V2-Flash
Avg Score:73.4%(+0.3%)
Providers:0