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GLM 5.2 vs Qwen3 Next 80B A3B Instruct

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 5.2

Tool calling

Context window

1.0M

1,048,576 tokens · ~786K words

Model page
Alibaba

Model

Qwen3 Next 80B A3B Instruct

Tool calling

Context window

262K

262,144 tokens · ~197K 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 5.21.0M
Qwen3 Next 80B A3B Instruct262K

GLM 5.2 has about 4× the context window of the other in this pair.

GLM 5.2 has 300% more context capacity (1048K vs 262K tokens).

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use GLM 5.2. Its 1048K context fits entire documents without chunking (vs 262K).

Full specs

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

SpecGLM 5.2Qwen3 Next 80B A3B Instruct
Context window1,048,576 tokens (1048K)262,144 tokens (262K)
Max output tokens131,072 tokens (131K)N/A
Speed tierBalancedFast
VisionNoNo
Function callingYesYes
Extended thinkingYesNo
Prompt cachingYesNo
Batch APINoNo
Release dateJun 2026Sep 2025

Frequently asked questions

GLM 5.2 has a larger context window: 1048K tokens vs 262K. 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