Context Window

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Kimi K2.5 vs Kimi K2p6

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 K2.5

Image inputTool calling

Context window

262K

262,144 tokens · ~197K words

Model page
Moonshot

Model

Kimi K2p6

Image inputTool calling

Context window

262K

262,144 tokens · ~197K 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 K2.5262K
Kimi K2p6262K

Same context window size for both models.

Token calculator →Memory savings →

Kimi K2.5 and Kimi K2p6 have identical context windows (262K tokens). Kimi K2.5 is 36% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • RAG / high-volume retrieval

    Use Kimi K2.5. Input tokens are 36% 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 K2.5Kimi K2p6
Context window262,144 tokens (262K)262,144 tokens (262K)
Max output tokens262,144 tokens (262K)262,144 tokens (262K)
Speed tierBalancedBalanced
VisionYesYes
Function callingYesYes
Extended thinkingYesYes
Prompt cachingYesYes
Batch APINoNo
Release dateJan 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.

ProviderKimi K2.5 inKimi K2.5 outKimi K2p6 inKimi K2p6 out
Azure$0.600/M$3.00/M——
Baseten$0.600/M$3.00/M——
Fireworks——$0.950/M$4.00/M
Moonshot$0.600/M$3.00/M——
Openrouter$0.600/M$3.00/M——
Together Ai$0.500/M$2.80/M——

Frequently asked questions

Kimi K2p6 has a larger context window: 262K 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.

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