Context Window

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GPT-4o Search Preview vs Gpt 5 2 Chat 2025 12 11

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-4o Search Preview

Image inputTool calling

Context window

128K

128,000 tokens · ~96K words

Model page
Openai

Model

Gpt 5 2 Chat 2025 12 11

Image inputTool 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.

GPT-4o Search Preview128K
Gpt 5 2 Chat 2025 12 11128K

Same context window size for both models.

Token calculator →Memory savings →

GPT-4o Search Preview and Gpt 5 2 Chat 2025 12 11 have identical context windows (128K tokens). Gpt 5 2 Chat 2025 12 11 is 30% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • RAG / high-volume retrieval

    Use Gpt 5 2 Chat 2025 12 11. Input tokens are 30% cheaper — critical when sending large retrieved contexts.

Full specs

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

SpecGPT-4o Search PreviewGpt 5 2 Chat 2025 12 11
Context window128,000 tokens (128K)128,000 tokens (128K)
Max output tokens16,384 tokens (16K)16,384 tokens (16K)
Speed tierBalancedBalanced
VisionYesYes
Function callingYesYes
Extended thinkingNoYes
Prompt cachingYesYes
Batch APIYesNo
Release dateMar 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.

ProviderGPT-4o Search Preview inGPT-4o Search Preview outGpt 5 2 Chat 2025 12 11 inGpt 5 2 Chat 2025 12 11 out
Azure——$1.75/M$14.00/M
Openai$2.50/M$10.00/M——

Frequently asked questions

Gpt 5 2 Chat 2025 12 11 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.

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