Context Window

Compare

Glm 4 7 Fp8 vs Gpt 5 1 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 7 Fp8

Context window

203K

202,752 tokens · ~152K words

Model page
Openai

Model

Gpt 5 1 Chat Latest

Image input

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 7 Fp8203K
Gpt 5 1 Chat Latest128K

Glm 4 7 Fp8 has about 1.6× the context window of the other in this pair.

Token calculator →Memory savings →

Glm 4 7 Fp8 has 58% more context capacity (202K vs 128K tokens). Glm 4 7 Fp8 is 68% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Glm 4 7 Fp8. Its 202K context fits entire documents without chunking (vs 128K).

  • RAG / high-volume retrieval

    Use Glm 4 7 Fp8. Input tokens are 68% cheaper — critical when sending large retrieved contexts.

Full specs

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

SpecGlm 4 7 Fp8Gpt 5 1 Chat Latest
Context window202,752 tokens (202K)128,000 tokens (128K)
Max output tokens16,384 tokens (16K)16,384 tokens (16K)
Speed tierBalancedBalanced
VisionNoYes
Function callingNoNo
Extended thinkingNoYes
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 7 Fp8 inGlm 4 7 Fp8 outGpt 5 1 Chat Latest inGpt 5 1 Chat Latest out
Gmi$0.400/M$2.00/M——
Openai——$1.25/M$10.00/M

Frequently asked questions

Glm 4 7 Fp8 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.

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