Context Window

Compare

Jp Anthropic Claude Sonnet 4 5 20250929 vs Mistral Mixtral 8x7b Instruct

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.

Anthropic

Model

Jp Anthropic Claude Sonnet 4 5 20250929

Image inputTool calling

Context window

200K

200,000 tokens · ~150K words

Model page
Mistral

Model

Mistral Mixtral 8x7b Instruct

Context window

32K

32,000 tokens · ~24K 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.

Jp Anthropic Claude Sonnet 4 5 20250929200K
Mistral Mixtral 8x7b Instruct32K

Jp Anthropic Claude Sonnet 4 5 20250929 has about 6.3× the context window of the other in this pair.

Token calculator →Memory savings →

Jp Anthropic Claude Sonnet 4 5 20250929 has 525% more context capacity (200K vs 32K tokens). Mistral Mixtral 8x7b Instruct is 82% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Jp Anthropic Claude Sonnet 4 5 20250929. Its 200K context fits entire documents without chunking (vs 32K).

  • RAG / high-volume retrieval

    Use Mistral Mixtral 8x7b Instruct. Input tokens are 82% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Jp Anthropic Claude Sonnet 4 5 20250929. Its 64K 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.

SpecJp Anthropic Claude Sonnet 4 5 20250929Mistral Mixtral 8x7b Instruct
Context window200,000 tokens (200K)32,000 tokens (32K)
Max output tokens64,000 tokens (64K)8,191 tokens (8K)
Speed tierBalancedFast
VisionYesNo
Function callingYesNo
Extended thinkingYesNo
Prompt cachingYesNo
Batch APIYesNo
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.

ProviderJp Anthropic Claude Sonnet 4 5 20250929 inJp Anthropic Claude Sonnet 4 5 20250929 outMistral Mixtral 8x7b Instruct inMistral Mixtral 8x7b Instruct out
Aws Bedrock$3.30/M$16.50/M$0.590/M$0.910/M

Frequently asked questions

Jp Anthropic Claude Sonnet 4 5 20250929 has a larger context window: 200K 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.

Powered by Mem0

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