Context Window

Compare

Command A+ vs GLM 4.7 Flash

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.

Cohere

Model

Command A+

Image inputTool calling

Context window

192K

192,000 tokens · ~144K words

Model page
Z Ai

Model

GLM 4.7 Flash

Image inputTool calling

Context window

200K

200,000 tokens · ~150K 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.

Command A+192K
GLM 4.7 Flash200K

GLM 4.7 Flash has about 1× the context window of the other in this pair.

Token calculator →Memory savings →

GLM 4.7 Flash has 4% more context capacity (200K vs 192K tokens).

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use GLM 4.7 Flash. Its 200K context fits entire documents without chunking (vs 192K).

  • Long output (reports, code files)

    Use Command A+. Its 64K 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.

SpecCommand A+GLM 4.7 Flash
Context window192,000 tokens (192K)200,000 tokens (200K)
Max output tokens64,000 tokens (64K)32,000 tokens (32K)
Speed tierBalancedFast
VisionYesYes
Function callingYesYes
Extended thinkingYesYes
Prompt cachingYesYes
Batch APINoNo
Release dateSep 2026Jan 2026

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.

ProviderCommand A+ inCommand A+ outGLM 4.7 Flash inGLM 4.7 Flash out
Cloudflare——$0.060/M$0.400/M
Deepinfra——$0.060/M$0.400/M
Novita——$0.070/M$0.400/M
Openrouter$0.300/M$1.50/M$0.060/M$0.400/M
Z Ai————

Frequently asked questions

GLM 4.7 Flash has a larger context window: 200K tokens vs 192K. 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.
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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.

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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