Context Window

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Meta Llama3 1 70b Instruct vs Mistral Large 3

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.

Meta

Model

Meta Llama3 1 70b Instruct

Tool calling

Context window

128K

128,000 tokens · ~96K words

Model page
Mistral

Model

Mistral Large 3

Image inputTool calling

Context window

256K

256,000 tokens · ~192K 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.

Meta Llama3 1 70b Instruct128K
Mistral Large 3256K

Mistral Large 3 has about 2× the context window of the other in this pair.

Token calculator →Memory savings →

Mistral Large 3 has 100% more context capacity (256K vs 128K tokens). Mistral Large 3 is 49% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Mistral Large 3. Its 256K context fits entire documents without chunking (vs 128K).

  • RAG / high-volume retrieval

    Use Mistral Large 3. Input tokens are 49% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Mistral Large 3. Its 8K 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.

SpecMeta Llama3 1 70b InstructMistral Large 3
Context window128,000 tokens (128K)256,000 tokens (256K)
Max output tokens2,048 tokens (2K)8,191 tokens (8K)
Speed tierDeepDeep
VisionNoYes
Function callingYesYes
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.

ProviderMeta Llama3 1 70b Instruct inMeta Llama3 1 70b Instruct outMistral Large 3 inMistral Large 3 out
Aws Bedrock$0.990/M$0.990/M——
Azure——$0.500/M$1.50/M
Mistral——$0.500/M$1.50/M

Frequently asked questions

Mistral Large 3 has a larger context window: 256K tokens vs 128K. 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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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