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meta-llama의 파비콘

Meta: Llama Guard 4 12B

meta-llama/llama-guard-4-12b

모델 가중치
비교

Llama Guard 4 is a Llama 4 Scout-derived multimodal pretrained model, fine-tuned for content safety classification. Similar to previous versions, it can be used to classify content in both LLM inputs (prompt classification) and in LLM responses (response classification). It acts as an LLM—generating text in its output that indicates whether a given prompt or response is safe or unsafe, and if unsafe, it also lists the content categories violated.

Llama Guard 4 was aligned to safeguard against the standardized MLCommons hazards taxonomy and designed to support multimodal Llama 4 capabilities. Specifically, it combines features from previous Llama Guard models, providing content moderation for English and multiple supported languages, along with enhanced capabilities to handle mixed text-and-image prompts, including multiple images. Additionally, Llama Guard 4 is integrated into the Llama Moderations API, extending robust safety classification to text and images.

모달리티
입력 / 출력 가격
US$0.18 / US$0.181M당
컨텍스트
164K
출시일
2025년 4월 30일
지식 기준일
2024년 8월
비교
제공업체요금성능가동 시간앱활동자주 묻는 질문탐색

제공업체

여러 회사가 동일한 모델을 호스팅합니다. OpenRouter는 선택한 라우팅 모드인 Balanced(가격 + 속도), Nitro(가장 빠름), Floor(가장 저렴함)에 따라 해당 회사 중 한 곳으로 요청을 라우팅합니다.

요금

고객이 이 모델에 실제로 지불하는 평균 가격을 제공업체가 게시한 가격과 나란히 표시합니다. 캐싱과 할인으로 인해 실제 지불 가격은 정가보다 훨씬 낮은 경우가 많습니다.

성능

처리량은 모델의 출력 속도입니다(초당 토큰 수 — 높을수록 좋습니다). 지연 시간은 전체 왕복 시간입니다(낮을수록 좋습니다). TTFT는 첫 토큰까지 걸리는 시간, 즉 출력이 나타나기까지 걸리는 시간입니다(낮을수록 좋습니다).

가동 시간

가동 시간은 지난 3일 동안 하나 이상의 제공업체가 요청에 응답한 시간의 비율입니다. 가용성은 추론이 성공적으로 제공된 시간의 비율입니다. OpenRouter는 지속적으로 모니터링하며 제공업체가 오류를 반환하면 차선의 제공업체를 사용합니다.

앱

이 모델에 가장 많은 트래픽을 보내는 공개 앱입니다. 실제 프로덕션 워크로드의 모습을 보여주는 유용한 지표이자 이 모델이 어떤 사용 사례에 가장 적합한지 알려주는 단서입니다.

활동

시간에 따른 이 모델의 토큰 사용량 및 요청 트래픽.

API

이 모델을 호출하는 데 바로 사용할 수 있는 코드입니다. OpenRouter의 API는 OpenAI와 호환되므로 대부분의 SDK는 기본 URL만 바꾸면 작동합니다. 모델 간에 달라지는 것은 아래 모델 슬러그뿐입니다.

현재 EU 역내 라우팅을 통해 사용할 수 없습니다. 리전 내 라우팅 문서

더 많은 모델 탐색

비전 기능을 갖춘 AI 모델: 이미지 이해를 위한 멀티모달 LLM컬렉션AI 모델 순위순위
지연 시간 / 처리량
US$0.180US$0.1800.28s46 tps
99.12%
Priority
US$0.270US$0.2700.25s42 tps
98.45%
Standard 라우팅에서 사용되지 않음:이 엔드포인트가 사용되지 않는 이유
Flex
US$0.144US$0.144----
--
처리량
46토큰/초

P50, 제공업체 중 최고

지연 시간
0.25초

P50, 최상의 제공업체

가동 시간 (3일)모델에 연결할 수 있었습니다. 요청이 제공업체로 라우팅되었습니다.
100.00%
가용성(3일)모델이 제공업체 중 한 곳에서 추론 결과를 반환했습니다. 오류와 빈 응답은 실패로 집계됩니다.
99.17%

지난 3일간 가용성

최근 72시간
가용성 99.17%
3일 전2일 전어제현재

지난 24시간 동안의 가용성

OpenRouter Availability
99.45%

업스트림 제공업체에서 오류가 발생하면 요청 필터가 허용하는 경우 정상 상태인 다른 제공업체로 라우팅하여 복구할 수 있습니다. 제공업체별 가동 시간 데이터에 프로그래밍 방식으로 액세스할 때 사용하는 API는 엔드포인트 API입니다. 자세히 알아볼 수 있는 관련 옵션은 부하 분산 및 제공업체 라우팅 옵션입니다.

1.
https://api.builtwithai.in/의 파비콘
ai-product-playbook-llamaguard
신규
106M토큰
2.
https://api.whatgoesaroundcomesaround.in/의 파비콘
ai-product-playbook-llamaguard
신규
85.7M토큰
3.
https://sagabound.com/의 파비콘
SagaBound
신규
81.5M토큰
4.
https://www.tripletaco.ai/의 파비콘
tripletaco
신규
69.6M토큰
5.
https://app.extenteam.com/의 파비콘
ExtenTeam-LlamaGuard
신규
45.9M토큰

자주 묻는 질문

Llama Guard 4 is a Llama 4 Scout-derived multimodal pretrained model, fine-tuned for content safety classification. Similar to previous versions, it can be used to classify content in both LLM inputs (prompt classification) and in LLM responses (response classification).

Llama Guard 4 12B의 비용은 US$0.18/M 입력 토큰 및 US$0.18/백만 출력 토큰입니다.

Llama Guard 4 12B의 컨텍스트 윈도우는 163,840토큰입니다. 최대 16,384개의 완성 토큰을 지원합니다.

아니요. Llama Guard 4 12B은 tools를 지원하지 않으므로 함수 호출을 사용할 수 없습니다. response_format을 지원하지 않으므로 JSON 출력이 강제되지 않습니다.

Llama Guard 4 12B은(는) 이미지 및 텍스트을(를) 입력으로 받아 텍스트을(를) 반환합니다.

Llama 4 Maverick, Llama 4 Scout, Llama 3.3 70B Instruct 외 4개은(는) Meta Llama의 다른 텍스트 모델입니다.

Llama Guard 4 12B의 출시일은 2025년 4월 30일입니다. 지식 기준일은 2024년 8월 31일입니다.

다음 제작사의 다른 모델: Meta Llama

Llama 3.3 8B Instruct

A lightweight and ultra-fast variant of Llama 3.3 70B, for use when quick response times are needed most.

텍스트128K 컨텍스트
Llama 4 Maverick

Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model from Meta, built on a mixture-of-experts (MoE) architecture with 128 experts and 17 billion active parameters per forward pass (400B total). It supports multilingual text and image input, and produces multilingual text and code output across 12 supported languages. Optimized for vision-language tasks, Maverick is instruction-tuned for assistant-like behavior, image reasoning, and general-purpose multimodal interaction.

Maverick features early fusion for native multimodality and a 1 million token context window. It was trained on a curated mixture of public, licensed, and Meta-platform data, covering ~22 trillion tokens, with a knowledge cutoff in August 2024. Released on April 5, 2025 under the Llama 4 Community License, Maverick is suited for research and commercial applications requiring advanced multimodal understanding and high model throughput.

텍스트524K 컨텍스트US$0.1875 / US$0.6525
Llama 4 Scout

Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input (text and image) and multilingual output (text and code) across 12 supported languages. Designed for assistant-style interaction and visual reasoning, Scout uses 16 experts per forward pass and features a context length of 10 million tokens, with a training corpus of ~40 trillion tokens.

Built for high efficiency and local or commercial deployment, Llama 4 Scout incorporates early fusion for seamless modality integration. It is instruction-tuned for use in multilingual chat, captioning, and image understanding tasks. Released under the Llama 4 Community License, it was last trained on data up to August 2024 and launched publicly on April 5, 2025.

텍스트1.3M 컨텍스트US$0.10 / US$0.30
Llama Guard 3 8B

Llama Guard 3 is a Llama-3.1-8B pretrained model, fine-tuned for content safety classification. Similar to previous versions, it can be used to classify content in both LLM inputs (prompt classification) and in LLM responses (response classification). It acts as an LLM – it generates text in its output that indicates whether a given prompt or response is safe or unsafe, and if unsafe, it also lists the content categories violated.

Llama Guard 3 was aligned to safeguard against the MLCommons standardized hazards taxonomy and designed to support Llama 3.1 capabilities. Specifically, it provides content moderation in 8 languages, and was optimized to support safety and security for search and code interpreter tool calls.

텍스트
Llama 3.3 70B Instruct

The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out). The Llama 3.3 instruction tuned text only model is optimized for multilingual dialogue use cases and outperforms many of the available open source and closed chat models on common industry benchmarks.

Supported languages: English, German, French, Italian, Portuguese, Hindi, Spanish, and Thai.

Model Card

텍스트131K 컨텍스트US$0.10 / US$0.32
Llama 3.2 90B Vision Instruct

The Llama 90B Vision model is a top-tier, 90-billion-parameter multimodal model designed for the most challenging visual reasoning and language tasks. It offers unparalleled accuracy in image captioning, visual question answering, and advanced image-text comprehension. Pre-trained on vast multimodal datasets and fine-tuned with human feedback, the Llama 90B Vision is engineered to handle the most demanding image-based AI tasks.

This model is perfect for industries requiring cutting-edge multimodal AI capabilities, particularly those dealing with complex, real-time visual and textual analysis.

Click here for the original model card.

Usage of this model is subject to Meta's Acceptable Use Policy.

텍스트131K 컨텍스트
Llama 3.2 3B Instruct

Llama 3.2 3B is a 3-billion-parameter multilingual large language model, optimized for advanced natural language processing tasks like dialogue generation, reasoning, and summarization. Designed with the latest transformer architecture, it supports eight languages, including English, Spanish, and Hindi, and is adaptable for additional languages.

Trained on 9 trillion tokens, the Llama 3.2 3B model excels in instruction-following, complex reasoning, and tool use. Its balanced performance makes it ideal for applications needing accuracy and efficiency in text generation across multilingual settings.

Click here for the original model card.

Usage of this model is subject to Meta's Acceptable Use Policy.

텍스트131K 컨텍스트US$0.05 / US$0.33
Llama 3.2 1B Instruct

Llama 3.2 1B is a 1-billion-parameter language model focused on efficiently performing natural language tasks, such as summarization, dialogue, and multilingual text analysis. Its smaller size allows it to operate efficiently in low-resource environments while maintaining strong task performance.

Supporting eight core languages and fine-tunable for more, Llama 1.3B is ideal for businesses or developers seeking lightweight yet powerful AI solutions that can operate in diverse multilingual settings without the high computational demand of larger models.

Click here for the original model card.

Usage of this model is subject to Meta's Acceptable Use Policy.

텍스트60K 컨텍스트US$0.027 / US$0.201
Llama 3.2 11B Vision Instruct

Llama 3.2 11B Vision is a multimodal model with 11 billion parameters, designed to handle tasks combining visual and textual data. It excels in tasks such as image captioning and visual question answering, bridging the gap between language generation and visual reasoning. Pre-trained on a massive dataset of image-text pairs, it performs well in complex, high-accuracy image analysis.

Its ability to integrate visual understanding with language processing makes it an ideal solution for industries requiring comprehensive visual-linguistic AI applications, such as content creation, AI-driven customer service, and research.

Click here for the original model card.

Usage of this model is subject to Meta's Acceptable Use Policy.

텍스트131K 컨텍스트
Llama 3.1 405B

Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This is the base 405B pre-trained version.

It has demonstrated strong performance compared to leading closed-source models in human evaluations.

To read more about the model release, click here. Usage of this model is subject to Meta's Acceptable Use Policy.

텍스트131K 컨텍스트
Llama 3.1 405B Instruct

The highly anticipated 400B class of Llama3 is here! Clocking in at 128k context with impressive eval scores, the Meta AI team continues to push the frontier of open-source LLMs.

Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 405B instruct-tuned version is optimized for high quality dialogue usecases.

It has demonstrated strong performance compared to leading closed-source models including GPT-4o and Claude 3.5 Sonnet in evaluations.

To read more about the model release, click here. Usage of this model is subject to Meta's Acceptable Use Policy.

텍스트131K 컨텍스트
Llama 3.1 70B Instruct

Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 70B instruct-tuned version is optimized for high quality dialogue usecases.

It has demonstrated strong performance compared to leading closed-source models in human evaluations.

To read more about the model release, click here. Usage of this model is subject to Meta's Acceptable Use Policy.

텍스트131K 컨텍스트US$0.40 / US$0.40
Llama 3.1 8B Instruct

Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 8B instruct-tuned version is fast and efficient.

It has demonstrated strong performance compared to leading closed-source models in human evaluations.

To read more about the model release, click here. Usage of this model is subject to Meta's Acceptable Use Policy.

텍스트131K 컨텍스트US$0.02 / US$0.04
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.

To read more about the model release, click here. Usage of this model is subject to Meta's Acceptable Use Policy.

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Llama 3 8B

Meta's latest class of model (Llama 3) launched with a variety of sizes & flavors. This is the base 8B pre-trained version.

It has demonstrated strong performance compared to leading closed-source models in human evaluations.

To read more about the model release, click here. Usage of this model is subject to Meta's Acceptable Use Policy.

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Meta's latest class of model (Llama 3) launched with a variety of sizes & flavors. This is the base 70B pre-trained version.

It has demonstrated strong performance compared to leading closed-source models in human evaluations.

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Meta's latest class of model (Llama 3) launched with a variety of sizes & flavors. This 70B instruct-tuned version was optimized for high quality dialogue usecases.

It has demonstrated strong performance compared to leading closed-source models in human evaluations.

To read more about the model release, click here. Usage of this model is subject to Meta's Acceptable Use Policy.

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Llama 3 8B Instruct

Meta's latest class of model (Llama 3) launched with a variety of sizes & flavors. This 8B instruct-tuned version was optimized for high quality dialogue usecases.

It has demonstrated strong performance compared to leading closed-source models in human evaluations.

To read more about the model release, click here. Usage of this model is subject to Meta's Acceptable Use Policy.

텍스트8K 컨텍스트
CodeLlama 70B Instruct

Code Llama is a family of large language models for code. This one is based on Llama 2 70B and provides zero-shot instruction-following ability for programming tasks.

텍스트2K 컨텍스트
CodeLlama 34B Instruct

Code Llama is built upon Llama 2 and excels at filling in code, handling extensive input contexts, and following programming instructions without prior training for various programming tasks.

텍스트8K 컨텍스트