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Model comparison

Gemini 2.5 Pro vs DeepSeek R1 0528

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

Provider
Google / DeepSeek
global / china
Context
1M / 163.8K
text+image+file->text / text->text
Input price
$1.25 / $0.45
per 1M tokens
Output price
$10.00 / $2.15
per 1M tokens
Left model
Gemini 2.5 Pro
Google
FamilyGemini
Modalitytext+image+file->text

企业多模态和搜索增强场景常用型号。

Right model
DeepSeek R1 0528
DeepSeek
FamilyR1
Modalitytext->text

推理能力强,是中国站高热度推理模型入口之一。

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, DeepSeek R1 0528 is cheaper on combined input and output, but real routing, discounts, and limits still matter.

Gemini 2.5 Pro 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.

  • Gemini 2.5 Pro is worth checking first when the Gemini family, 1M context, and text+image+file->text capability match the job.
  • DeepSeek R1 0528 is worth checking first when the R1 family, 163.8K context, and text->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.

  • Google: Gemini 2.5 Pro, Gemini, text+image+file->text
  • DeepSeek: DeepSeek R1 0528, R1, text->text

Commercial fit

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

  • Gemini 2.5 Pro: 企业多模态和搜索增强场景常用型号。
  • DeepSeek R1 0528: 推理能力强,是中国站高热度推理模型入口之一。