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Glm 4 6:exacto vs Gpt 5 2 Chat Latest

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 4 6:exacto

Tool calling

Context window

203K

202,800 tokens · ~152K words

Model page
Openai

Model

Gpt 5 2 Chat Latest

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 4 6:exacto203K
Gpt 5 2 Chat Latest128K

Glm 4 6:exacto has about 1.6× the context window of the other in this pair.

Glm 4 6:exacto has 58% more context capacity (202K vs 128K tokens). Glm 4 6:exacto is 74% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Glm 4 6:exacto. Its 202K context fits entire documents without chunking (vs 128K).

  • RAG / high-volume retrieval

    Use Glm 4 6:exacto. Input tokens are 74% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Glm 4 6:exacto. Its 131K 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 4 6:exactoGpt 5 2 Chat Latest
Context window202,800 tokens (202K)128,000 tokens (128K)
Max output tokens131,000 tokens (131K)16,384 tokens (16K)
Speed tierBalancedBalanced
VisionNoYes
Function callingYesYes
Extended thinkingYesYes
Prompt cachingNoYes
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.

ProviderGlm 4 6:exacto inGlm 4 6:exacto outGpt 5 2 Chat Latest inGpt 5 2 Chat Latest out
Openai$1.75/M$14.00/M
Openrouter$0.450/M$1.90/M

Frequently asked questions

Glm 4 6:exacto has a larger context window: 202K 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.

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