Context Window

Compare

GLM 4.7 Flash vs Qwen2 5 32b

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 Flash

Image inputTool calling

Context window

200K

200,000 tokens · ~150K words

Model page
Alibaba

Model

Qwen2 5 32b

Tool 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 4.7 Flash200K
Qwen2 5 32b128K

GLM 4.7 Flash has about 1.6× the context window of the other in this pair.

Token calculator →Memory savings →

GLM 4.7 Flash has 56% more context capacity (200K vs 128K tokens). Qwen2 5 32b is 14% cheaper on input.

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 128K).

  • RAG / high-volume retrieval

    Use Qwen2 5 32b. Input tokens are 14% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Qwen2 5 32b. Its 128K 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 4.7 FlashQwen2 5 32b
Context window200,000 tokens (200K)128,000 tokens (128K)
Max output tokens32,000 tokens (32K)128,000 tokens (128K)
Speed tierFastBalanced
VisionYesNo
Function callingYesYes
Extended thinkingYesNo
Prompt cachingYesNo
Batch APINoNo
Release dateJan 2026N/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 Flash inGLM 4.7 Flash outQwen2 5 32b inQwen2 5 32b out
Nebius——$0.060/M$0.200/M
Openrouter$0.070/M$0.400/M——

Frequently asked questions

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

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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