Context Window

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Devstral 2 2512 vs Gpt 4o Realtime Preview

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 2 2512

Tool calling

Context window

256K

256,000 tokens · ~192K words

Model page
Openai

Model

Gpt 4o Realtime Preview

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 2 2512256K
Gpt 4o Realtime Preview128K

Devstral 2 2512 has about 2× the context window of the other in this pair.

Token calculator →Memory savings →

Devstral 2 2512 has 100% more context capacity (256K vs 128K tokens). Devstral 2 2512 is 92% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Devstral 2 2512. Its 256K context fits entire documents without chunking (vs 128K).

  • RAG / high-volume retrieval

    Use Devstral 2 2512. Input tokens are 92% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Devstral 2 2512. 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 2 2512Gpt 4o Realtime Preview
Context window256,000 tokens (256K)128,000 tokens (128K)
Max output tokens256,000 tokens (256K)4,096 tokens (4K)
Speed tierBalancedBalanced
VisionNoNo
Function callingYesYes
Extended thinkingNoNo
Prompt cachingYesYes
Batch APINoYes
Release dateDec 2025N/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 2 2512 inDevstral 2 2512 outGpt 4o Realtime Preview inGpt 4o Realtime Preview out
Mistral$0.400/M$2.00/M——
Openai——$5.00/M$20.00/M
Openrouter$0.150/M$0.600/M——

Frequently asked questions

Devstral 2 2512 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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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