Context Window

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Meta Llama3 1 8b Instruct vs O1 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

Meta Llama3 1 8b Instruct

Tool calling

Context window

128K

128,000 tokens · ~96K words

Model page
Openai

Model

O1 Mini

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.

Meta Llama3 1 8b Instruct128K
O1 Mini128K

Same context window size for both models.

Token calculator →Memory savings →

Meta Llama3 1 8b Instruct and O1 Mini have identical context windows (128K tokens). Meta Llama3 1 8b Instruct is 80% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • RAG / high-volume retrieval

    Use Meta Llama3 1 8b Instruct. Input tokens are 80% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use O1 Mini. Its 65K 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.

SpecMeta Llama3 1 8b InstructO1 Mini
Context window128,000 tokens (128K)128,000 tokens (128K)
Max output tokens2,048 tokens (2K)65,536 tokens (65K)
Speed tierFastFast
VisionNoNo
Function callingYesYes
Extended thinkingNoYes
Prompt cachingNoYes
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.

ProviderMeta Llama3 1 8b Instruct inMeta Llama3 1 8b Instruct outO1 Mini inO1 Mini out
Aws Bedrock$0.220/M$0.220/M——
Azure——$1.21/M$4.84/M
Replicate——$1.10/M$4.40/M

Frequently asked questions

O1 Mini has a larger context window: 128K 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