Context Window

Compare

Gpt 4o Audio Preview 2025 06 03 vs GPT-4o-mini Search 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.

Openai

Model

Gpt 4o Audio Preview 2025 06 03

Tool calling

Context window

128K

128,000 tokens · ~96K words

Model page
Openai

Model

GPT-4o-mini Search Preview

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 Audio Preview 2025 06 03128K
GPT-4o-mini Search Preview128K

Same context window size for both models.

Token calculator →Memory savings →

Gpt 4o Audio Preview 2025 06 03 and GPT-4o-mini Search Preview have identical context windows (128K tokens). GPT-4o-mini Search Preview is 94% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • RAG / high-volume retrieval

    Use GPT-4o-mini Search Preview. Input tokens are 94% 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 Audio Preview 2025 06 03GPT-4o-mini Search Preview
Context window128,000 tokens (128K)128,000 tokens (128K)
Max output tokens16,384 tokens (16K)16,384 tokens (16K)
Speed tierBalancedFast
VisionNoYes
Function callingYesYes
Extended thinkingNoNo
Prompt cachingNoYes
Batch APIYesYes
Release dateN/AMar 2025

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 Audio Preview 2025 06 03 inGpt 4o Audio Preview 2025 06 03 outGPT-4o-mini Search Preview inGPT-4o-mini Search Preview out
Openai$2.50/M$10.00/M$0.150/M$0.600/M

Frequently asked questions

GPT-4o-mini Search 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.

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