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 tokens | $0.600/ 1M tokens |
“—” means the modality is not billed in that direction, or the vendor has not published a price for it.
Benchmark Results
Llama 4 Maverick currently shows benchmark results led by MBPP (22 / 96, score 77.60), MMLU (40 / 124, score 85.50), MMMU (39 / 74, score 73.40). 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
6 evaluationsCoding and Software Engineer
3 evaluationsMath and Reasoning
3 evaluationsMultimodal Understanding
3 evaluationsAgent Level Benchmark
4 evaluationsPublisher
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.
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