A hyper-specialized, ultra-cheap safety classifier — indispensable in the right pipeline, useless outside of it.
0
Coding
0
Writing
30
Research
0
Images
90
Value
45
Long Context
Use this when
Automated content safety screening and moderation for AI application pipelines at minimal cost.
Skip this if
You need a general-purpose AI assistant for coding, writing, research, or any task beyond binary or categorical content safety classification.
Pricing
$0.48/1M in
$0.03/1M out
→0%since May 2026
Context
131k tokens
Speed
Very fast
This model is designed exclusively for content moderation and safety classification tasks. It follows the MLCommons AI Safety benchmark taxonomy. It should be deployed as a guardrail layer alongside generative models, not as a replacement for them. Not suitable for end-user-facing conversational applications.
Extremely low cost at $0.02/$0.06 per 1M tokens makes it viable for high-volume moderation tasks
Purpose-trained on MLCommons hazard taxonomy with strong classification accuracy for harmful content categories
128K context window allows screening of long conversations or documents in a single pass
Fast inference due to compact 8B parameter size, enabling real-time moderation with low latency
Weaknesses
Not a general-purpose model — cannot generate text, answer questions, or assist with coding or writing tasks
May produce false positives or miss nuanced edge cases compared to more sophisticated safety systems like Anthropic's Constitutional AI classifiers
Limited to safety classification use cases; deploying it outside moderation pipelines offers no value
Real-world use cases
What people actually use Llama Guard 3 8B for.
Screening user-submitted prompts before passing them to a generative model to block policy violations
Classifying AI-generated outputs for harmful content categories before delivering responses to end users
Auditing large conversation logs or datasets for safety compliance in research or enterprise deployments
How Llama Guard 3 8B compares
The nearest models people weigh against it, and what actually separates them.
vs Llama 3.1 70B Instruct — Against Llama 3.1 70B Instruct (Meta), Llama Guard 3 8B runs about 36% cheaper per token and answers faster. Take Llama Guard 3 8B unless you specifically need what Llama 3.1 70B Instruct does better.
vs Llama 3.2 11B Vision Instruct — Against Llama 3.2 11B Vision Instruct (Meta), Llama Guard 3 8B runs about 26% cheaper per token and answers faster. Take Llama Guard 3 8B unless you specifically need what Llama 3.2 11B Vision Instruct does better.
vs Llama 4 Maverick — Against Llama 4 Maverick (Meta), Llama Guard 3 8B runs about 77% cheaper per token, gives up 2x on context and answers faster. Take Llama Guard 3 8B unless you specifically need what Llama 4 Maverick does better.
Price History
Llama Guard 3 8B pricing over time
→0% since May 30
90 data points · tracked daily since May 30, 2026
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Start using Llama Guard 3 8B
Automated content safety screening and moderation for AI application pipelines at minimal cost.. Start free — no card required.
Meta's Llama 3.1 70B Instruct is a open-weight large language model with 70 billion parameters, fine-tuned for instruction following across coding, reasoning, and general-purpose tasks. It offers a strong balance of capability and cost at $0.40/1M tokens for both input and output.
Verdict
The go-to budget open-weight model for teams who need solid LLM capability without frontier model pricing.
Quality score
65%
Pricing
$0.40/1M in
$0.40/1M out
Speed
Fast
4/5 speed
Context
131k tokens
Pricing shown is via third-party API providers (e.g., OpenRouter, Together AI) — costs may vary. Meta releases Llama 3.1 weights publicly, enabling self-hosting at even lower cost. Not available directly from Meta as a hosted API.
Llama 3.2 11B Vision Instruct is Meta's open-weight multimodal model capable of understanding both text and images at an extremely low price point. It handles image captioning, visual question answering, and document analysis alongside standard text tasks.
Verdict
The go-to vision model when budget is the top constraint and good-enough accuracy is acceptable.
Quality score
57%
Pricing
$0.34/1M in
$0.34/1M out
Speed
Fast
4/5 speed
Context
131k tokens
Available via multiple inference providers including Together AI, Fireworks, and OpenRouter. As an open-weight model, it can also be self-hosted for even lower marginal costs at scale. Part of Meta's Llama 3.2 family which also includes a 90B vision variant for heavier workloads.
Open-weightVisionBudgetMultimodalMeta
Best for
Budget-conscious developers who need basic vision capabilities without paying premium multimodal prices.
Llama Guard 3 8B (Meta) is now indexed. A hyper-specialized, ultra-cheap safety classifier — indispensable in the right pipeline, useless outside of it.
Llama Guard 3 8B costs $0.48 per million input tokens and $0.03 per million output tokens on the API. A month of 10M input and 2M output tokens runs about $4.86 at list price, before any batch or caching discounts.
What is Llama Guard 3 8B best for?
Llama Guard 3 8B is best for automated content safety screening and moderation for ai application pipelines at minimal cost.. It is a strong fit when that workflow matters more than the tradeoffs around budget pricing and very fast speed.
When should I avoid Llama Guard 3 8B?
You need a general-purpose AI assistant for coding, writing, research, or any task beyond binary or categorical content safety classification.
What is a cheaper alternative to Llama Guard 3 8B?
Mistral Small 3.1 (Mistral) at $0.10/1M/1M input against Llama Guard 3 8B's $0.48/1M/1M — roughly 22% less per token all in. Ultra-cheap multimodal model for massive-volume, low-complexity pipelines. Compare it first if Llama Guard 3 8B's pricing is the thing stopping you.
What is a faster alternative to Llama Guard 3 8B?
Llama 3.1 70B Instruct — fast against Llama Guard 3 8B's very fast, with 131k tokens of context. Worth the swap when response time is what your users notice rather than the last few points of reasoning depth.
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