Context Window

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Anthropic Claude vs Mistral Small 2503

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

Anthropic Claude

Context window

100K

100,000 tokens · ~75K words

Model page
Mistral

Model

Mistral Small 2503

Image inputTool calling

Context window

128K

128,000 tokens · ~96K 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.

Anthropic Claude100K
Mistral Small 2503128K

Mistral Small 2503 has about 1.3× the context window of the other in this pair.

Token calculator →Memory savings →

Mistral Small 2503 has 28% more context capacity (128K vs 100K tokens). Mistral Small 2503 is 98% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Mistral Small 2503. Its 128K context fits entire documents without chunking (vs 100K).

  • RAG / high-volume retrieval

    Use Mistral Small 2503. Input tokens are 98% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Mistral Small 2503. Its 128K 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.

SpecAnthropic ClaudeMistral Small 2503
Context window100,000 tokens (100K)128,000 tokens (128K)
Max output tokens8,191 tokens (8K)128,000 tokens (128K)
Speed tierBalancedBalanced
VisionNoYes
Function callingNoYes
Extended thinkingNoNo
Prompt cachingNoNo
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.

ProviderAnthropic Claude inAnthropic Claude outMistral Small 2503 inMistral Small 2503 out
Aws Bedrock$8.00/M$24.00/M——
Azure——$0.100/M$0.300/M
Google Vertex——$1.00/M$3.00/M
Ibm Watsonx——$0.100/M$0.300/M

Frequently asked questions

Mistral Small 2503 has a larger context window: 128K tokens vs 100K. 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