Context Window

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Llama Guard 4 12B vs Open Mistral Nemo 2407

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 Guard 4 12B

Image input

Context window

164K

163,840 tokens · ~123K words

Model page
Mistral

Model

Open Mistral Nemo 2407

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 Guard 4 12B164K
Open Mistral Nemo 2407128K

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

Token calculator →Memory savings →

Llama Guard 4 12B has 28% more context capacity (163K vs 128K tokens). Llama Guard 4 12B is 40% 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 Llama Guard 4 12B. Input tokens are 40% 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.

SpecLlama Guard 4 12BOpen Mistral Nemo 2407
Context window163,840 tokens (163K)128,000 tokens (128K)
Max output tokens163,840 tokens (163K)128,000 tokens (128K)
Speed tierBalancedBalanced
VisionYesNo
Function callingNoNo
Extended thinkingNoNo
Prompt cachingNoNo
Batch APINoNo
Release dateApr 2025N/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 Guard 4 12B inLlama Guard 4 12B outOpen Mistral Nemo 2407 inOpen Mistral Nemo 2407 out
Deepinfra$0.180/M$0.180/M——
Groq$0.200/M$0.200/M——
Mistral——$0.300/M$0.300/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.

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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.

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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