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DeepSeek-R1 vs Devstral-2-123B
Comprehensive side-by-side LLM comparison
Devstral-2-123B offers 128.2K more tokens in context window than DeepSeek-R1. DeepSeek-R1 is $1.26 cheaper per million tokens. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-R1, released by DeepSeek on January 20, 2025, is a large reasoning model with 671 billion total parameters (37 billion active in its MoE architecture) designed for extended chain-of-thought reasoning. It features a 128K token context window and demonstrated strong performance on mathematics, coding, and scientific reasoning benchmarks at its release. DeepSeek-R1 targets complex analytical tasks, competitive programming, and applications requiring deep deliberative reasoning 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.
10 months newer
DeepSeek-R1
DeepSeek
2025-01-20
Devstral-2-123B
Mistral AI
2025-12-09
Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-R1
Input:$0.55
Output:$2.19($1.26 cheaper)
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Devstral-2-123B
Input:$1.00
Output:$3.00
Performance Metrics
Context window and performance specifications
Provider Availability & Performance
Available providers and their performance metrics
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DeepSeek-R1
1 providers
DeepSeek
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Devstral-2-123B
1 providers
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DeepSeek-R1
Avg Score:0.0%
Providers:1
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Devstral-2-123B
Avg Score:0.0%
Providers:1