Compare

Gpt 4o Mini Audio Preview vs Llama Guard 4 12B

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.

Openai

Model

Gpt 4o Mini Audio Preview

Tool calling

Context window

128K

128,000 tokens · ~96K words

Model page
Meta

Model

Llama Guard 4 12B

Image input

Context window

164K

163,840 tokens · ~123K 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.

Gpt 4o Mini Audio Preview128K
Llama Guard 4 12B164K

Llama Guard 4 12B has about 1.3× the context window of the other in this pair.

Llama Guard 4 12B has 28% more context capacity (163K vs 128K tokens). Gpt 4o Mini Audio Preview is 16% cheaper on input.

Quick verdicts

Short takeaways — validate with your own workloads.

  • Long document processing

    Use Llama Guard 4 12B. Its 163K context fits entire documents without chunking (vs 128K).

  • RAG / high-volume retrieval

    Use Gpt 4o Mini Audio Preview. Input tokens are 16% cheaper — critical when sending large retrieved contexts.

  • Long output (reports, code files)

    Use Llama Guard 4 12B. Its 163K 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.

SpecGpt 4o Mini Audio PreviewLlama Guard 4 12B
Context window128,000 tokens (128K)163,840 tokens (163K)
Max output tokens16,384 tokens (16K)163,840 tokens (163K)
Speed tierFastBalanced
VisionNoYes
Function callingYesNo
Extended thinkingNoNo
Prompt cachingNoNo
Batch APIYesNo
Release dateN/AApr 2025

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.

ProviderGpt 4o Mini Audio Preview inGpt 4o Mini Audio Preview outLlama Guard 4 12B inLlama Guard 4 12B out
Deepinfra$0.180/M$0.180/M
Groq$0.200/M$0.200/M
Openai$0.150/M$0.600/M

Frequently asked questions

Llama Guard 4 12B has a larger context window: 163K 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.

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