Context Window

Compare

MiniMax M2.7 vs Moonshotai Kimi K3 1

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.

Minimax

Model

MiniMax M2.7

Tool calling

Context window

205K

204,800 tokens · ~154K words

Model page
Moonshot

Model

Moonshotai Kimi K3 1

Image inputTool calling

Context window

869K

868,928 tokens · ~652K 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.

MiniMax M2.7205K
Moonshotai Kimi K3 1869K

Moonshotai Kimi K3 1 has about 4.2× the context window of the other in this pair.

Token calculator →Memory savings →

Moonshotai Kimi K3 1 has 324% more context capacity (868K vs 204K tokens). MiniMax M2.7 is 95% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Moonshotai Kimi K3 1. Its 868K context fits entire documents without chunking (vs 204K).

  • RAG / high-volume retrieval

    Use MiniMax M2.7. Input tokens are 95% cheaper — critical when sending large retrieved contexts.

Full specs

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

SpecMiniMax M2.7Moonshotai Kimi K3 1
Context window204,800 tokens (204K)868,928 tokens (868K)
Max output tokens131,072 tokens (131K)131,072 tokens (131K)
Speed tierFastBalanced
VisionNoYes
Function callingYesYes
Extended thinkingYesYes
Prompt cachingYesYes
Batch APINoNo
Release dateMar 2026N/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.

ProviderMiniMax M2.7 inMiniMax M2.7 outMoonshotai Kimi K3 1 inMoonshotai Kimi K3 1 out
Aws Bedrock——$4.40/M$22.00/M
Deepinfra$0.250/M$1.00/M——
Gmi$0.210/M$0.840/M——
Novita$0.300/M$1.20/M——
Openrouter$0.210/M$0.840/M——
Sambanova$0.600/M$2.40/M——
Together Ai$0.300/M$1.20/M——

Frequently asked questions

Moonshotai Kimi K3 1 has a larger context window: 868K tokens vs 204K. For long documents, large codebases, or extended agent sessions, the larger context window reduces the need to chunk inputs or summarize history.

Powered by Mem0

Use a smaller model.
Get better results.

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.

Calculate your savingsLearn about Mem0

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