llama-4-maverick-instruct - AI Model Guide

Llama-4-maverick-instruct is Meta's instruction-tuned large language model from the Llama 4 generation. It features 17 billion active parameters and a Mixture-of-Experts architecture with 128 expert modules, designed for high-performance text generation, reasoning, code assistance, and multilingual tasks.

Llama 4 Maverick Instruct has 17 billion active parameters. It uses a Mixture-of-Experts (MoE) architecture with 128 expert modules, meaning only a subset of parameters are activated per inference, making it computationally efficient while maintaining strong performance.

Mixture-of-Experts (MoE) is an architecture where the model routes each input token through a subset of specialized expert networks rather than the full model. Llama 4 Maverick uses 128 expert modules, activating only 17B parameters per forward pass, which improves efficiency and scalability compared to dense models.

Llama 4 Maverick Instruct supports advanced text generation, logical reasoning, summarization, creative writing, code writing and debugging, multilingual translation, question answering, and multi-turn conversational dialogue. It is well-suited for enterprise applications, developer tools, content creation, and research workflows.

Llama 4 Maverick Instruct is Meta's flagship instruction-tuned variant in the Llama 4 family, optimized for following complex instructions with high fidelity. Its MoE architecture with 128 experts differentiates it by balancing depth and computational efficiency, making it a strong choice for production-scale deployments.

Llama 4 Maverick Instruct was created by Meta, the AI research division behind the Llama model family. It is available on CRAISEE via the Replicate provider under the model slug meta/llama-4-maverick-instruct, and has accumulated over 6.2 million runs on the platform.

Yes, Llama 4 Maverick Instruct supports code assistance across major programming languages. It can write new code, explain existing code, and debug errors. Its strong instruction-following capability makes it effective for structured coding prompts, making it a reliable choice for developers on CRAISEE.

Llama 4 Maverick Instruct has been run over 6,249,842 times on CRAISEE, making it one of the most widely used large language models on the platform. This high usage reflects its reliability and versatility across creative, professional, and technical use cases.