Context Window

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Mistral Mixtral 8x7b Instruct vs Moonshotai Kimi K2 5

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.

Mistral

Model

Mistral Mixtral 8x7b Instruct

Context window

32K

32,000 tokens · ~24K words

Model page
Moonshot

Model

Moonshotai Kimi K2 5

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.

Mistral Mixtral 8x7b Instruct32K
Moonshotai Kimi K2 5262K

Moonshotai Kimi K2 5 has about 8.2× the context window of the other in this pair.

Token calculator →Memory savings →

Moonshotai Kimi K2 5 has 719% more context capacity (262K vs 32K tokens). Mistral Mixtral 8x7b Instruct is 18% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Moonshotai Kimi K2 5. Its 262K context fits entire documents without chunking (vs 32K).

  • RAG / high-volume retrieval

    Use Mistral Mixtral 8x7b Instruct. Input tokens are 18% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Moonshotai Kimi K2 5. Its 262K 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.

SpecMistral Mixtral 8x7b InstructMoonshotai Kimi K2 5
Context window32,000 tokens (32K)262,144 tokens (262K)
Max output tokens8,191 tokens (8K)262,144 tokens (262K)
Speed tierFastBalanced
VisionNoYes
Function callingNoYes
Extended thinkingNoNo
Prompt cachingNoNo
Batch APINoNo
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.

ProviderMistral Mixtral 8x7b Instruct inMistral Mixtral 8x7b Instruct outMoonshotai Kimi K2 5 inMoonshotai Kimi K2 5 out
Aws Bedrock$0.590/M$0.910/M$0.720/M$3.60/M

Frequently asked questions

Moonshotai Kimi K2 5 has a larger context window: 262K tokens vs 32K. 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