Context Window

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Llama 4 Scout 17b 16e vs Openai Gpt 4o Mini

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

Image inputTool calling

Context window

10M

10,000,000 tokens · ~7.5M words

Model page
Openai

Model

Openai Gpt 4o Mini

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 16e10M
Openai Gpt 4o Mini128K

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

Token calculator →Memory savings →

Llama 4 Scout 17b 16e 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. 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 16eOpenai Gpt 4o Mini
Context window10,000,000 tokens (10000K)128,000 tokens (128K)
Max output tokens16,384 tokens (16K)N/A
Speed tierFastFast
VisionYesNo
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 inLlama 4 Scout 17b 16e outOpenai Gpt 4o Mini inOpenai Gpt 4o Mini out
Azure$0.200/M$0.780/M——
Deepinfra$0.080/M$0.300/M——
Gradient————
Groq$0.110/M$0.340/M——
Lambda$0.050/M$0.100/M——
Novita$0.180/M$0.590/M——
Nscale$0.090/M$0.290/M——
Sambanova$0.400/M$0.700/M——
Together Ai$0.180/M$0.590/M——

Frequently asked questions

Llama 4 Scout 17b 16e 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.

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Without Mem0~128K tokens sent
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Repeated info
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