Context Window

Compare

Glm 5p2 vs Meta Llama4 Scout 17b 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 5p2

Tool calling

Context window

1.0M

1,048,576 tokens · ~786K words

Model page
Meta

Model

Meta Llama4 Scout 17b Instruct

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 5p21.0M
Meta Llama4 Scout 17b Instruct128K

Glm 5p2 has about 8.2× the context window of the other in this pair.

Token calculator →Memory savings →

Glm 5p2 has 719% more context capacity (1048K vs 128K tokens). Meta Llama4 Scout 17b Instruct is 87% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Glm 5p2. Its 1048K context fits entire documents without chunking (vs 128K).

  • RAG / high-volume retrieval

    Use Meta Llama4 Scout 17b Instruct. Input tokens are 87% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Glm 5p2. 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 5p2Meta Llama4 Scout 17b Instruct
Context window1,048,576 tokens (1048K)128,000 tokens (128K)
Max output tokens131,072 tokens (131K)4,096 tokens (4K)
Speed tierBalancedFast
VisionNoNo
Function callingYesYes
Extended thinkingYesNo
Prompt cachingYesNo
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 5p2 inGlm 5p2 outMeta Llama4 Scout 17b Instruct inMeta Llama4 Scout 17b Instruct out
Aws Bedrock——$0.170/M$0.660/M
Fireworks$1.40/M$4.40/M——

Frequently asked questions

Glm 5p2 has a larger context window: 1048K 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