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DeepSeek V4 Pro vs MiMo-V2.5-Pro

A side-by-side comparison of two llm models — real specs, pricing, strengths and weaknesses, and a clear verdict on which to choose. Kept current by our agents.

Quick verdict: which should you choose?

Choose DeepSeek V4 Pro if you need

  • higher intelligence and coding/STEM performance (51.5 index)
  • faster generation at 79.81 tokens per second
  • open-weight model for local or custom deployment
  • clear, structured outputs on technical tasks

Choose MiMo-V2.5-Pro if you need

  • proprietary Xiaomi-hosted deployment
  • focus on long-form text processing at 1M context
  • identical per-token pricing to DeepSeek
  • pure text modality without additional features

Verdict

DeepSeek V4 Pro leads with a substantially higher intelligence_index (51.5 vs 35.6) and nearly 50% faster output speed while matching MiMo-V2.5-Pro on price and 1M-token context. It also offers open-weight access and documented strengths in coding and STEM tasks. MiMo-V2.5-Pro remains a viable proprietary alternative only when users specifically need Xiaomi's ecosystem or long-form text processing without performance benchmarks.

DeepSeek V4 Pro vs MiMo-V2.5-Pro: side by side

SpecDeepSeek V4 ProMiMo-V2.5-ProWinner
Intelligence51.535.6DeepSeek V4 Pro
Output speed80 t/s52 t/sDeepSeek V4 Pro
Output price$0.87/1M$0.87/1MTie
Context1049K1049KTie
ParamsTie
TypeOpen-weightProprietaryTie
ProviderDeepSeekXiaomiTie

Detailed analysis

Intelligence

Winner: DeepSeek V4 Pro

DeepSeek V4 Pro scores 51.5 on the intelligence_index compared with MiMo-V2.5-Pro's 35.6. Its listed strengths explicitly include strong coding performance and technical/STEM domains, while MiMo lists only general long-text handling.

Speed

Winner: DeepSeek V4 Pro

DeepSeek V4 Pro outputs at 79.81 tokens per second versus MiMo-V2.5-Pro's 52.2 t/s. Both share the same 1M context length, so the speed difference directly affects throughput on large inputs.

Pricing & Context

Winner: Tie

Both models charge $0.87 per million output tokens and support exactly 1,048,576-token contexts. No pricing or context-length advantage exists for either.

Access & Modality

Winner: DeepSeek V4 Pro

DeepSeek V4 Pro is open-weight while MiMo-V2.5-Pro is proprietary. Both are text-only with no vision or real-time capabilities listed.

DeepSeek V4 Pro

Pros

  • +Strong performance on coding tasks
  • +Effective handling of very long inputs
  • +Clear and structured outputs
  • +Good at technical and STEM domains

Cons

  • Text-only modality
  • No real-time information access
  • Can produce hallucinations on facts
Full DeepSeek V4 Pro review →

MiMo-V2.5-Pro

Pros

  • +Supports up to 1M token context
  • +Strong at processing large text inputs
  • +Suitable for long-form tasks
  • +Pure text LLM focus

Cons

  • Text modality only
  • No vision or multimodal support
  • Large context may increase latency
Full MiMo-V2.5-Pro review →

Summary: DeepSeek V4 Pro vs MiMo-V2.5-Pro

Select DeepSeek V4 Pro when intelligence, speed, or open weights matter. Choose MiMo-V2.5-Pro only if a proprietary Xiaomi solution is required and lower measured performance is acceptable. Both are otherwise comparable on cost and context size.

Frequently asked questions

DeepSeek V4 Pro is stronger on the provided intelligence_index and speed metrics plus open-weight access.

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