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MiniMax M2.5 vs DeepSeek V4

Comprehensive comparison between MiniMax's MiniMax M2.5 and DeepSeek's DeepSeek V4. Compare pricing, performance, features, and user reviews.

minimax vs deepseekminimax vs deepseek v4chinese ai comparison国产模型对比

Specs Comparison

SpecificationMiniMax M2.5DeepSeek V4
Context Window197K1000K
Max Output32K66K
Input (per 1M tokens)$0.30$0.14
Output (per 1M tokens)$2.40$0.28
Reasoning
Open Source

Scenario Score Comparison

MiniMax M2.5

Pros

  • + Extremely cheap ($0.20/1M input)
  • + Strong tool calling & function calling
  • + 197K context window
  • + Excellent agentic performance
  • + Supports Shell, Browser, Python, MCP

Cons

  • Less known in Western markets
  • Documentation mainly in Chinese
  • Smaller ecosystem than Claude/GPT
  • Rate limits on free tier

DeepSeek V4

Pros

  • + 1M token context window
  • + Native multimodal (text/image/video)
  • + Price 1/20th of proprietary models
  • + Open-source & self-hostable
  • + Matches frontier model performance

Cons

  • Servers in China (latency for overseas users)
  • Geopolitical supply chain concerns
  • Self-hosting requires significant hardware

Recommendation

Choose MiniMax M2.5 if you:

  • Need extremely cheap ($0.20/1m input)
  • Need strong tool calling & function calling
  • Need 197k context window

Choose DeepSeek V4 if you:

  • Need 1m token context window
  • Need native multimodal (text/image/video)
  • Need price 1/20th of proprietary models

Based on scores across 0 scenarios, both models perform equally well.

Get Started with MiniMax M2.5

1Visit the provider's website
2Create an account
3Start using the model

Get Started with DeepSeek V4

1Visit the provider's website
2Create an account
3Start using the model

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