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Model comparison

o4-mini vs Mistral Large 3

Not a benchmark table. This puts pricing, context, interface fit, and key visibility into one decision card.

Provider
OpenAI / Mistral AI
global / global
Context
200K / 262.1K
text+image->text / text+image->text
Input price
$1.10 / $2.00
per 1M tokens
Output price
$4.40 / $6.00
per 1M tokens
Left model
o4-mini
OpenAI
Familyo-series
Modalitytext+image->text

适合推理型产品化调用和代理场景。

Right model
Mistral Large 3
Mistral AI
FamilyMistral
Modalitytext+image->text

欧洲系旗舰模型,速度与成本平衡感很好。

Comparison summary

How to choose first

This is a cross-provider comparison. Start with the job boundary, then verify what your key can actually see.

On the listed price snapshot, o4-mini is cheaper on combined input and output, but real routing, discounts, and limits still matter.

Mistral Large 3 has the larger context window, which helps with long documents, knowledge bases, logs, and multi-turn workflows.

Decision boundary

Do not start with which model is absolutely stronger. Start with the boundary: cost, context, speed, quality, ecosystem, or supply stability.

  • o4-mini is worth checking first when the o-series family, 200K context, and text+image->text capability match the job.
  • Mistral Large 3 is worth checking first when the Mistral family, 262.1K context, and text+image->text capability match the job.

Key checking route

If you already hold a key, the valuable check is provider identity, callable models, and whether balance, limits, or subscription status are visible.

  • OpenAI: o4-mini, o-series, text+image->text
  • Mistral AI: Mistral Large 3, Mistral, text+image->text

Commercial fit

Commercially, do not look at model names alone. Combine price, limits, region, upstream stability, and ongoing monitoring.

  • o4-mini: 适合推理型产品化调用和代理场景。
  • Mistral Large 3: 欧洲系旗舰模型,速度与成本平衡感很好。