Context Window

Compare

Glm 4p5 Air vs GPT-4o 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.

Z Ai

Model

Glm 4p5 Air

Tool calling

Context window

128K

128,000 tokens · ~96K words

Model page
Openai

Model

GPT-4o 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.

Glm 4p5 Air128K
GPT-4o Search Preview128K

Same context window size for both models.

Token calculator →Memory savings →

Glm 4p5 Air and GPT-4o Search Preview have identical context windows (128K tokens). Glm 4p5 Air is 91% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • RAG / high-volume retrieval

    Use Glm 4p5 Air. Input tokens are 91% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Glm 4p5 Air. Its 96K 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.

SpecGlm 4p5 AirGPT-4o Search Preview
Context window128,000 tokens (128K)128,000 tokens (128K)
Max output tokens96,000 tokens (96K)16,384 tokens (16K)
Speed tierBalancedBalanced
VisionNoYes
Function callingYesYes
Extended thinkingYesNo
Prompt cachingNoYes
Batch APINoYes
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.

ProviderGlm 4p5 Air inGlm 4p5 Air outGPT-4o Search Preview inGPT-4o Search Preview out
Fireworks$0.220/M$0.880/M——
Openai——$2.50/M$10.00/M

Frequently asked questions

GPT-4o 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