Context Window

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Deepseek V3 2 251201 vs Mistral Large

This page is context-first: how much text each model can take in one request. Full specs adds capabilities and limits; the pricing matrix below is only about $/million tokens from hosts that list both models.

Deepseek

Model

Deepseek V3 2 251201

Tool calling

Context window

98K

98,304 tokens · ~74K words

Model page
Mistral

Model

Mistral Large

Tool calling

Context window

32K

32,000 tokens · ~24K words

Model page

Context window · side by side

Bar length is relative to the larger of the two windows (100% = max of this pair). This is not pricing.

Deepseek V3 2 25120198K
Mistral Large32K

Deepseek V3 2 251201 has about 3.1× the context window of the other in this pair.

Token calculator →Memory savings →

Deepseek V3 2 251201 has 207% more context capacity (98K vs 32K tokens).

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Deepseek V3 2 251201. Its 98K context fits entire documents without chunking (vs 32K).

  • Long output (reports, code files)

    Use Deepseek V3 2 251201. Its 32K max output lets you generate complete artifacts in one request.

Full specs

Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.

SpecDeepseek V3 2 251201Mistral Large
Context window98,304 tokens (98K)32,000 tokens (32K)
Max output tokens32,768 tokens (32K)8,191 tokens (8K)
Speed tierBalancedDeep
VisionNoNo
Function callingYesYes
Extended thinkingYesNo
Prompt cachingNoYes
Batch APINoNo
Release dateN/AFeb 2024

Pricing matrix

Dollar rates only: hosts that list both models, per 1M tokens. For how much text fits, use the context section above — not this table.

ProviderDeepseek V3 2 251201 inDeepseek V3 2 251201 outMistral Large inMistral Large out
Azure——$4.00/M$12.00/M
Ibm Watsonx——$3.00/M$10.00/M
Openrouter——$8.00/M$24.00/M
Snowflake————
Volcengine————

Frequently asked questions

Deepseek V3 2 251201 has a larger context window: 98K tokens vs 32K. For long documents, large codebases, or extended agent sessions, the larger context window reduces the need to chunk inputs or summarize history.

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