Context Window

Compare

Gpt Realtime 1 5 2026 02 23 vs Open Mistral 7b

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.

Openai

Model

Gpt Realtime 1 5 2026 02 23

Tool calling

Context window

32K

32,000 tokens · ~24K words

Model page
Mistral

Model

Open Mistral 7b

Context window

32K

32,000 tokens · ~24K 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.

Gpt Realtime 1 5 2026 02 2332K
Open Mistral 7b32K

Same context window size for both models.

Token calculator →Memory savings →

Gpt Realtime 1 5 2026 02 23 and Open Mistral 7b have identical context windows (32K tokens). Open Mistral 7b is 93% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • RAG / high-volume retrieval

    Use Open Mistral 7b. Input tokens are 93% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Open Mistral 7b. 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.

SpecGpt Realtime 1 5 2026 02 23Open Mistral 7b
Context window32,000 tokens (32K)32,000 tokens (32K)
Max output tokens4,096 tokens (4K)8,191 tokens (8K)
Speed tierBalancedFast
VisionNoNo
Function callingYesNo
Extended thinkingNoNo
Prompt cachingYesNo
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.

ProviderGpt Realtime 1 5 2026 02 23 inGpt Realtime 1 5 2026 02 23 outOpen Mistral 7b inOpen Mistral 7b out
Azure$4.00/M$16.00/M——
Mistral——$0.250/M$0.250/M

Frequently asked questions

Open Mistral 7b has a larger context window: 32K tokens vs 32K. 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