Context Window

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Command R (08-2024) vs Gpt 4o Mini 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.

Cohere

Model

Command R (08-2024)

Tool calling

Context window

128K

128,000 tokens · ~96K words

Model page
Openai

Model

Gpt 4o Mini 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.

Command R (08-2024)128K
Gpt 4o Mini Realtime Preview128K

Same context window size for both models.

Token calculator →Memory savings →

Command R (08-2024) and Gpt 4o Mini Realtime Preview have identical context windows (128K tokens). Command R (08-2024) is 75% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • RAG / high-volume retrieval

    Use Command R (08-2024). Input tokens are 75% cheaper — critical when sending large retrieved contexts.

Full specs

Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.

SpecCommand R (08-2024)Gpt 4o Mini Realtime Preview
Context window128,000 tokens (128K)128,000 tokens (128K)
Max output tokens4,096 tokens (4K)4,096 tokens (4K)
Speed tierBalancedFast
VisionNoNo
Function callingYesYes
Extended thinkingNoNo
Prompt cachingNoYes
Batch APINoYes
Release dateAug 2024N/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.

ProviderCommand R (08-2024) inCommand R (08-2024) outGpt 4o Mini Realtime Preview inGpt 4o Mini Realtime Preview out
Cohere$0.150/M$0.600/M——
Openai——$0.600/M$2.40/M

Frequently asked questions

Gpt 4o Mini Realtime Preview has a larger context window: 128K 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.
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