Llama-4-Maverick-17B-128E
Llama-4-Maverick-17B-128E is an AI model published by Facebook AI Research Lab, released on 2025-04-05, for Multimodal model, with 400B parameters, and 1000K context length, requiring about 218GB storage, with a 85.50 score on MMLU.
Data sourced primarily from official releases (GitHub, Hugging Face, papers), then benchmark leaderboards, then third-party evaluators. Learn about our data methodology
Model basics
Open source & experience
Official resources
API details
| Type | Condition | Input | Output |
|---|---|---|---|
| Text | - | $0.150/ 1M | $0.600/ 1M |
Benchmark Results
Llama 4 Maverick currently shows benchmark results led by MBPP (13 / 28, score 77.60), MMLU (38 / 66, score 85.50), MATH (30 / 42, score 61.20). This page also consolidates core specs, context limits, and API pricing so you can evaluate the model from benchmark results and deployment constraints together.
General Knowledge
4 evaluationsMath and Reasoning
2 evaluationsCompare with other models
No curated comparisons for this model yet.
Want a custom combination? Open the compare tool
Publisher
Model Overview
Llama-4-Maverick-17B-128E is an AI model published by Facebook AI Research Lab, released on 2025-04-05, for Multimodal model, with 400B parameters, and 1000K context length, requiring about 218GB storage, with a 85.50 score on MMLU.
DataLearner on WeChat
Follow DataLearner on WeChat for AI model updates and research notes.
