Meta: LlamaGuard 2 8B
Analysis Summary
LlamaGuard 2 8B is a specialised Meta model intended for safety-oriented classification rather than general language generation. The supplied record lists text-only modality, an 8,192-token context window, and pricing of $0.20 per million input and output tokens. It contains no benchmark results and no documented tool or function-calling support.
Its likely role in an agency stack is as a narrow screening component placed before or after a generation model, provided task-specific policy testing confirms the required behaviour. It is not suitable as the primary model for client copy, SEO planning, document analysis, coding, or autonomous agents. The low price is useful for high-volume checks, but teams should validate coverage and false-positive behaviour before production deployment.
Assessed August 9, 2026
Editorial notes
LlamaGuard 2 8B is a specialized safety model with low operating cost, but it has no supplied benchmark data and should not be treated as a general content, coding, or reasoning model.
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DFO Verdict
LlamaGuard 2 8B is a specialized safety model with low operating cost, but it has no supplied benchmark data and should not be treated as a general content, coding, or reasoning model.
How Meta: LlamaGuard 2 8B compares
Its 8K-token context window is larger than 22% of the models we list. At $0.20 per million input tokens it is cheaper than 57% of comparable models.
Dark bar = input · light bar = output, scaled to the priciest peer.
1M tokens ≈ 8 full-length novels or ~2,500 pages of business documents in a single request.
Strongest on value. The pulled-in technical corner is the trade-off, and if the shape matters more than the price, this is your model.
Compare shapes side-by-side →Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.20 | $0.000200 |
| Output | $0.20 | $0.000200 |
What would Meta: LlamaGuard 2 8B cost your business?
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A website chatbot handling around 100 customer conversations a day, a few short messages each.
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These numbers get smaller with the right architecture.
We route routine calls to cheap models and save Meta: LlamaGuard 2 8B for the hard ones. Most clients cut their estimate by 60-80%.
Talk to our teamAbout Meta: LlamaGuard 2 8B
This safeguard model has 8B parameters and is based on the Llama 3 family. Just like is predecessor, LlamaGuard 1, it can do both prompt and response classification. LlamaGuard 2 acts as a normal LLM would, generating text that indicates whether the given input/output is safe/unsafe. If deemed unsafe, it will also share the content categories violated. For best results, please use raw prompt input or the /completions endpoint, instead of the chat API. It has demonstrated strong performance compared to leading closed-source models in human evaluations. Usage of this model is subject to Meta's Acceptable Use Policy.
Frequently asked questions about Meta: LlamaGuard 2 8B
How much does Meta: LlamaGuard 2 8B cost?
Meta: LlamaGuard 2 8B costs $0.20 per million input tokens and $0.20 per million output tokens.
What is the context window of Meta: LlamaGuard 2 8B?
Meta: LlamaGuard 2 8B has a context window of 8,192 tokens (8K).
Who created Meta: LlamaGuard 2 8B?
Meta: LlamaGuard 2 8B is developed by Meta and was released on May 13, 2024.
