Context Window

Compare

GLM 4.7 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.

Z Ai

Model

GLM 4.7

Image inputTool calling

Context window

203K

202,752 tokens · ~152K 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.

GLM 4.7203K
Moonshotai Kimi K3 1869K

Moonshotai Kimi K3 1 has about 4.3× the context window of the other in this pair.

Token calculator →Memory savings →

Moonshotai Kimi K3 1 has 328% more context capacity (868K vs 202K tokens). GLM 4.7 is 86% 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 202K).

  • RAG / high-volume retrieval

    Use GLM 4.7. Input tokens are 86% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Moonshotai Kimi K3 1. Its 131K 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.

SpecGLM 4.7Moonshotai Kimi K3 1
Context window202,752 tokens (202K)868,928 tokens (868K)
Max output tokens64,000 tokens (64K)131,072 tokens (131K)
Speed tierBalancedBalanced
VisionYesYes
Function callingYesYes
Extended thinkingYesYes
Prompt cachingYesYes
Batch APINoNo
Release dateDec 2025N/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.

ProviderGLM 4.7 inGLM 4.7 outMoonshotai Kimi K3 1 inMoonshotai Kimi K3 1 out
Aws Bedrock——$4.40/M$22.00/M
Baseten$0.600/M$2.20/M——
Deepinfra$0.400/M$1.75/M——
Novita$0.600/M$2.20/M——
Openrouter$0.600/M$2.20/M——
Together Ai$0.450/M$2.00/M——
Z Ai$0.600/M$2.20/M——

Frequently asked questions

Moonshotai Kimi K3 1 has a larger context window: 868K tokens vs 202K. 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