Context Window

Compare

Devstral Medium Latest vs Llama 3 3 70b Versatile

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

Devstral Medium Latest

Tool calling

Context window

256K

256,000 tokens · ~192K words

Model page
Meta

Model

Llama 3 3 70b Versatile

Tool 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.

Devstral Medium Latest256K
Llama 3 3 70b Versatile128K

Devstral Medium Latest has about 2× the context window of the other in this pair.

Token calculator →Memory savings →

Devstral Medium Latest has 100% more context capacity (256K vs 128K tokens). Devstral Medium Latest is 32% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Devstral Medium Latest. Its 256K context fits entire documents without chunking (vs 128K).

  • RAG / high-volume retrieval

    Use Devstral Medium Latest. Input tokens are 32% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Devstral Medium Latest. Its 256K 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.

SpecDevstral Medium LatestLlama 3 3 70b Versatile
Context window256,000 tokens (256K)128,000 tokens (128K)
Max output tokens256,000 tokens (256K)32,768 tokens (32K)
Speed tierBalancedDeep
VisionNoNo
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.

ProviderDevstral Medium Latest inDevstral Medium Latest outLlama 3 3 70b Versatile inLlama 3 3 70b Versatile out
Groq——$0.590/M$0.790/M
Mistral$0.400/M$2.00/M——

Frequently asked questions

Devstral Medium Latest 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