Context Window

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Kimi K2 7 Code Highspeed vs MiniMax M3.1 Flash

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.

Moonshot

Model

Kimi K2 7 Code Highspeed

Context window

262K

262,144 tokens · ~197K words

Model page
Minimax

Model

MiniMax M3.1 Flash

Image inputTool calling

Context window

1M

1,000,000 tokens · ~750K 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.

Kimi K2 7 Code Highspeed262K
MiniMax M3.1 Flash1M

MiniMax M3.1 Flash has about 3.8× the context window of the other in this pair.

Token calculator →Memory savings →

MiniMax M3.1 Flash has 281% more context capacity (1000K vs 262K tokens). MiniMax M3.1 Flash is 94% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use MiniMax M3.1 Flash. Its 1000K context fits entire documents without chunking (vs 262K).

  • RAG / high-volume retrieval

    Use MiniMax M3.1 Flash. Input tokens are 94% cheaper — critical when sending large retrieved contexts.

Full specs

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

SpecKimi K2 7 Code HighspeedMiniMax M3.1 Flash
Context window262,144 tokens (262K)1,000,000 tokens (1000K)
Max output tokensN/A524,288 tokens (524K)
Speed tierBalancedFast
VisionNoYes
Function callingNoYes
Extended thinkingNoYes
Prompt cachingYesYes
Batch APINoNo
Release dateN/AOct 2026

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.

ProviderKimi K2 7 Code Highspeed inKimi K2 7 Code Highspeed outMiniMax M3.1 Flash inMiniMax M3.1 Flash out
Gmi$1.90/M$8.00/M$0.113/M$0.450/M
Nebius——$0.150/M$0.600/M
Together Ai——$0.150/M$0.600/M

Frequently asked questions

MiniMax M3.1 Flash has a larger context window: 1000K tokens vs 262K. 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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Use a smaller model.
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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