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

1 benchmarks

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.

Sun Mar 15 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Sun Mar 15 2026 • llm-stats.com
DeepSeek
DeepSeek-V2.5
Input tokens$0.14
Output tokens$0.28
Best providerDeepSeek
MiniMax
MiniMax M1 40K
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
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Model Size

Parameter count comparison

220.0B diff

MiniMax M1 40K has 220.0B more parameters than DeepSeek-V2.5, making it 93.2% larger.

DeepSeek
DeepSeek-V2.5
236.0Bparameters
MiniMax
MiniMax M1 40K
456.0Bparameters
236.0B
DeepSeek-V2.5
456.0B
MiniMax M1 40K

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).

DeepSeek
DeepSeek-V2.5
Input8,192 tokens
Output8,192 tokens
MiniMax
MiniMax M1 40K
Input- tokens
Output- tokens
Sun Mar 15 2026 • llm-stats.com

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-V2.5

deepseek

Open weights

MiniMax M1 40K

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.

DeepSeek-V2.5

May 8, 2024

1.9 years ago

MiniMax M1 40K

Jun 16, 2025

9 months ago

1.1yr newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

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Key Takeaways

Larger context window (8,192 tokens)
Higher SWE-Bench Verified score (55.6% vs 16.8%)

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V2.5
MiniMax
MiniMax M1 40K