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Llama Guard 4 12B 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.
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 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).
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).
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | Llama Guard 4 12B | Openai Gpt 4o Mini |
|---|---|---|
| Context window | 163,840 tokens (163K) | 128,000 tokens (128K) |
| Max output tokens | 163,840 tokens (163K) | N/A |
| Speed tier | Balanced | Fast |
| Vision | Yes | No |
| Function calling | No | No |
| Extended thinking | No | No |
| Prompt caching | No | No |
| Batch API | No | Yes |
| Release date | Apr 2025 | N/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.
| Provider | Llama Guard 4 12B in | Llama Guard 4 12B out | Openai Gpt 4o Mini in | Openai Gpt 4o Mini out |
|---|---|---|---|---|
| Deepinfra | $0.180/M | $0.180/M | — | — |
| Gradient | — | — | — | — |
| Groq | $0.200/M | $0.200/M | — | — |
Frequently asked questions
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