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Llama 3.2 1B Instruct vs Llama Prompt Guard 2 22m
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 3.2 1B Instruct has about 117.2× the context window of the other in this pair.
Llama 3.2 1B Instruct has 11618% more context capacity (60K vs 0K tokens).
Quick verdicts
Short takeaways — validate with your own workloads.
Long document processing
Use Llama 3.2 1B Instruct. Its 60K context fits entire documents without chunking (vs 0K).
Full specs
Context, output, capabilities, and dates. Green highlights the favorable value where we compute a winner.
| Spec | Llama 3.2 1B Instruct | Llama Prompt Guard 2 22m |
|---|---|---|
| Context window | 60,000 tokens (60K) | 512 tokens (0K) |
| Max output tokens | N/A | 512 tokens (0K) |
| Speed tier | Fast | Balanced |
| Vision | No | No |
| Function calling | No | No |
| Extended thinking | No | No |
| Prompt caching | No | No |
| Batch API | No | No |
| Release date | Sep 2024 | 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 3.2 1B Instruct in | Llama 3.2 1B Instruct out | Llama Prompt Guard 2 22m in | Llama Prompt Guard 2 22m out |
|---|---|---|---|---|
| Groq | — | — | $0.030/M | $0.030/M |
Frequently asked questions
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Use a smaller model.
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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
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