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DeepSeek-V3.2 vs Devstral-2-123B
Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. Devstral-2-123B offers 128.2K more tokens in context window than DeepSeek-V3.2. DeepSeek-V3.2 is $2.63 cheaper per million tokens. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-V3.2, released by DeepSeek on December 1, 2025, is a large language model with 685 billion total parameters featuring integrated thinking in tool-use and support for both reasoning and direct generation modes. It features a 128K token context window and introduced large-scale agent training across 1,800+ environments. DeepSeek-V3.2 targets agentic workflows, complex instruction following, and coding tasks under an open MIT license.
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Mistral AI
Devstral 2, released by Mistral AI on December 9, 2025, is a 123 billion parameter dense transformer model specifically designed for software engineering tasks. It features a 256K token context window and achieved 72.2% on SWE-bench Verified at release, making it a competitive open-weight option for automated coding and agentic development. Devstral 2 targets code generation, multi-file software engineering, and agentic development workflows under a modified MIT license.
8 days newer
DeepSeek-V3.2
DeepSeek
2025-12-01
Devstral-2-123B
Mistral AI
2025-12-09
Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-V3.2
Input:$0.27
Output:$1.10($2.63 cheaper)
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Devstral-2-123B
Input:$1.00
Output:$3.00
Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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DeepSeek-V3.2
Average Score:37.5%
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Devstral-2-123B
Average Score:37.5%
Performance comparison across key benchmark categories
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DeepSeek-V3.2
Coding37.5%
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Devstral-2-123B
Coding37.5%
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek-V3.2
1 providers
DeepSeek
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Devstral-2-123B
1 providers
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DeepSeek-V3.2
Avg Score:37.5%
Providers:1
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Devstral-2-123B
Avg Score:37.5%
Providers:1