Context Window

Compare

Llama 4 Scout 17b 16e Instruct Maas vs Openai Gpt 4o

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.

Meta

Model

Llama 4 Scout 17b 16e Instruct Maas

Tool calling

Context window

10M

10,000,000 tokens · ~7.5M words

Model page
Openai

Model

Openai Gpt 4o

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.

Llama 4 Scout 17b 16e Instruct Maas10M
Openai Gpt 4o128K

Llama 4 Scout 17b 16e Instruct Maas has about 78.1× the context window of the other in this pair.

Token calculator →Memory savings →

Llama 4 Scout 17b 16e Instruct Maas has 7712% more context capacity (10000K vs 128K tokens).

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Llama 4 Scout 17b 16e Instruct Maas. Its 10000K context fits entire documents without chunking (vs 128K).

Full specs

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

SpecLlama 4 Scout 17b 16e Instruct MaasOpenai Gpt 4o
Context window10,000,000 tokens (10000K)128,000 tokens (128K)
Max output tokens10,000,000 tokens (10000K)N/A
Speed tierFastBalanced
VisionNoNo
Function callingYesNo
Extended thinkingNoNo
Prompt cachingNoNo
Batch APINoYes
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.

ProviderLlama 4 Scout 17b 16e Instruct Maas inLlama 4 Scout 17b 16e Instruct Maas outOpenai Gpt 4o inOpenai Gpt 4o out
Google Vertex$0.250/M$0.700/M——
Gradient————

Frequently asked questions

Llama 4 Scout 17b 16e Instruct Maas has a larger context window: 10000K 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