Context Window

Compare

Jp Anthropic Claude Sonnet 4 6 vs Kimi K2 Thinking 251104

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.

Anthropic

Model

Jp Anthropic Claude Sonnet 4 6

Image inputTool calling

Context window

1M

1,000,000 tokens · ~750K words

Model page
Moonshot

Model

Kimi K2 Thinking 251104

Tool calling

Context window

229K

229,376 tokens · ~172K 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.

Jp Anthropic Claude Sonnet 4 61M
Kimi K2 Thinking 251104229K

Jp Anthropic Claude Sonnet 4 6 has about 4.4× the context window of the other in this pair.

Token calculator →Memory savings →

Jp Anthropic Claude Sonnet 4 6 has 335% more context capacity (1000K vs 229K tokens).

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Jp Anthropic Claude Sonnet 4 6. Its 1000K context fits entire documents without chunking (vs 229K).

  • Long output (reports, code files)

    Use Jp Anthropic Claude Sonnet 4 6. Its 64K 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.

SpecJp Anthropic Claude Sonnet 4 6Kimi K2 Thinking 251104
Context window1,000,000 tokens (1000K)229,376 tokens (229K)
Max output tokens64,000 tokens (64K)32,768 tokens (32K)
Speed tierBalancedDeep
VisionYesNo
Function callingYesYes
Extended thinkingYesYes
Prompt cachingYesNo
Batch APIYesNo
Release dateN/AN/A

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.

ProviderJp Anthropic Claude Sonnet 4 6 inJp Anthropic Claude Sonnet 4 6 outKimi K2 Thinking 251104 inKimi K2 Thinking 251104 out
Aws Bedrock$3.30/M$16.50/M——
Volcengine————

Frequently asked questions

Jp Anthropic Claude Sonnet 4 6 has a larger context window: 1000K tokens vs 229K. 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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Mem0 gives your AI long-term memory so you stop re-sending context on every call. That means you can use a smaller, faster, cheaper model — and still get better answers.

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Example: a multi-turn chat session

Without Mem0~128K tokens sent
Full history
Repeated info
Old context
With Mem0~20K tokens sent
Key memories
Current turn

80% less to send — works with any model