DeepSeek-V2.5 vs MiniMax M1 40K Comparison
Comparing DeepSeek-V2.5 and MiniMax M1 40K across benchmarks, pricing, and capabilities.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V2.5 outperforms in 0 benchmarks, while MiniMax M1 40K is better at 1 benchmark (SWE-Bench Verified).
MiniMax M1 40K significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
Cost data unavailable.
Model Size
Parameter count comparison
MiniMax M1 40K has 220.0B more parameters than DeepSeek-V2.5, making it 93.2% larger.
Context Window
Maximum input and output token capacity
Only DeepSeek-V2.5 specifies input context (8,192 tokens). Only DeepSeek-V2.5 specifies output context (8,192 tokens).
License
Usage and distribution terms
DeepSeek-V2.5 is licensed under deepseek, while MiniMax M1 40K uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
deepseek
Open weights
MIT
Open weights
Release Timeline
When each model was launched
DeepSeek-V2.5 was released on 2024-05-08, while MiniMax M1 40K was released on 2025-06-16.
MiniMax M1 40K is 13 months newer than DeepSeek-V2.5.
May 8, 2024
1.9 years ago
Jun 16, 2025
9 months ago
1.1yr newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Key Takeaways
DeepSeek-V2.5
View detailsDeepSeek
MiniMax M1 40K
View detailsMiniMax
Detailed Comparison
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