# Meta Models via Hanzo AI — 12 models

> Access all 12 Meta models through Hanzo's OpenAI-compatible API. Single API key, unified billing, no rate limit juggling.

[Models](https://hanzo.ai/models)/Meta

# Meta Models via Hanzo AI

12 models available

Access all 12 Meta models through Hanzo's OpenAI-compatible API. One key, one bill, no rate limit juggling.

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[Meta: Llama 3.1 70B Instruct131KMeta'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...text](https://hanzo.ai/models/meta-llama/llama-3.1-70b-instruct)[Meta: Llama 3.1 8B Instruct131KMeta'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...text](https://hanzo.ai/models/meta-llama/llama-3.1-8b-instruct)[Meta: Llama 3.2 1B Instruct60KLlama 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...text](https://hanzo.ai/models/meta-llama/llama-3.2-1b-instruct)[Meta: Llama 3.2 3B Instruct131KLlama 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...text](https://hanzo.ai/models/meta-llama/llama-3.2-3b-instruct)[Meta: Llama 3.3 70B Instruct131KThe 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...text](https://hanzo.ai/models/meta-llama/llama-3.3-70b-instruct)[Meta: Llama 4 Maverick1MLlama 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...text](https://hanzo.ai/models/meta-llama/llama-4-maverick)[Meta: Llama 4 Scout1MLlama 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](https://hanzo.ai/models/meta-llama/llama-4-scout)[Meta: Llama Guard 4 12B164KLlama 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...text](https://hanzo.ai/models/meta-llama/llama-guard-4-12b)[Meta: Muse Glimmer 30B131KMuse Glimmer 30B is a dense, open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark and optimized for autonomous agents on consumer hardware. It is suited for long-horizon...text](https://hanzo.ai/models/meta/muse-glimmer-30b)[Meta: Muse Spark 1.11MMuse Spark 1.1 is a multimodal reasoning model from Meta, built for agentic tasks. It accepts text, images, video, audio, and PDF documents and returns text, with a 1M-token context...text](https://hanzo.ai/models/meta/muse-spark-1.1)[Meta: Muse Spark 1.21MMuse Spark 1.2 is a reasoning model from Meta, designed for complex agentic tasks. It accepts text, images, video, audio, and PDF documents, returns text, and offers a 1M-token context...text](https://hanzo.ai/models/meta/muse-spark-1.2)[Meta: Muse Spark 1.2 Contributor1MMuse Spark 1.2 contributor tier is a reasoning model from Meta designed for developers who want to start building at an even lower cost. It’s meaningfully cheaper than Muse Spark...text](https://hanzo.ai/models/meta/muse-spark-1.2-contributor)

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