Meta: Llama 4 Maverick

Text input Image input Text output
Author's Description

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.

Key Specifications
Cost
$$$
Context
1M
Parameters
17B
Released
Apr 05, 2025
Speed
Ability
Reliability
Supported Parameters

This model supports the following parameters:

Structured Outputs Response Format Stop Seed Min P Top P Max Tokens Frequency Penalty Temperature Presence Penalty
Features

This model supports the following features:

Response Format Structured Outputs
Performance Summary

Meta's Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model demonstrating strong overall performance, particularly in reliability and certain specialized tasks. The model consistently performs among the fastest, ranking in the 76th percentile for speed across benchmarks, and offers competitive pricing, placing in the 64th percentile. Notably, Maverick exhibits exceptional reliability with a 100% success rate across all evaluated benchmarks, indicating consistent and stable operation. In terms of specific performance, Maverick excels in Ethics and Mathematics, achieving perfect accuracy in Ethics and 94.5% in Mathematics, ranking in the 94th and 92nd percentiles respectively, often being the most accurate among models of comparable speed or price. It also shows strong performance in General Knowledge (99.3% accuracy) and Reasoning (80.0% accuracy). However, the model displays a notable weakness in Instruction Following, with only 30.3% accuracy, placing it in the 31st percentile. Its hallucination rate, while not the worst, is also a point for improvement at 88.0% accuracy (meaning 12% hallucination rate). Coding performance is moderate at 79.5%. Overall, Maverick is a robust model for multimodal understanding and generation, particularly suited for applications requiring high reliability and strong ethical or mathematical reasoning, though its instruction following capabilities may require further refinement.

Model Pricing

Current Pricing

Feature Price (per 1M tokens)
Prompt $0.15
Completion $0.6

Price History

Available Endpoints
Provider Endpoint Name Context Length Pricing (Input) Pricing (Output)
DeepInfra
DeepInfra | meta-llama/llama-4-maverick-17b-128e-instruct 1M $0.15 / 1M tokens $0.6 / 1M tokens
Parasail
Parasail | meta-llama/llama-4-maverick-17b-128e-instruct 1M $0.15 / 1M tokens $0.85 / 1M tokens
Kluster
Kluster | meta-llama/llama-4-maverick-17b-128e-instruct 1M $0.15 / 1M tokens $0.6 / 1M tokens
Novita
Novita | meta-llama/llama-4-maverick-17b-128e-instruct 1M $0.17 / 1M tokens $0.85 / 1M tokens
Lambda
Lambda | meta-llama/llama-4-maverick-17b-128e-instruct 1M $0.15 / 1M tokens $0.6 / 1M tokens
BaseTen
BaseTen | meta-llama/llama-4-maverick-17b-128e-instruct 1M $0.15 / 1M tokens $0.6 / 1M tokens
Cent-ML
Cent-ML | meta-llama/llama-4-maverick-17b-128e-instruct 1M $0.15 / 1M tokens $0.6 / 1M tokens
Groq
Groq | meta-llama/llama-4-maverick-17b-128e-instruct 131K $0.2 / 1M tokens $0.6 / 1M tokens
NCompass
NCompass | meta-llama/llama-4-maverick-17b-128e-instruct 400K $0.15 / 1M tokens $0.6 / 1M tokens
Fireworks
Fireworks | meta-llama/llama-4-maverick-17b-128e-instruct 1M $0.22 / 1M tokens $0.88 / 1M tokens
GMICloud
GMICloud | meta-llama/llama-4-maverick-17b-128e-instruct 1M $0.15 / 1M tokens $0.6 / 1M tokens
Together
Together | meta-llama/llama-4-maverick-17b-128e-instruct 1M $0.27 / 1M tokens $0.85 / 1M tokens
Google
Google | meta-llama/llama-4-maverick-17b-128e-instruct 524K $0.35 / 1M tokens $1.15 / 1M tokens
DeepInfra
DeepInfra | meta-llama/llama-4-maverick-17b-128e-instruct 8K $0.5 / 1M tokens $0.5 / 1M tokens
SambaNova
SambaNova | meta-llama/llama-4-maverick-17b-128e-instruct 131K $0.63 / 1M tokens $1.8 / 1M tokens
BaseTen
BaseTen | meta-llama/llama-4-maverick-17b-128e-instruct 1M $0.19 / 1M tokens $0.72 / 1M tokens
Friendli
Friendli | meta-llama/llama-4-maverick-17b-128e-instruct 131K $0.2 / 1M tokens $0.6 / 1M tokens
Cerebras
Cerebras | meta-llama/llama-4-maverick-17b-128e-instruct 32K $0.2 / 1M tokens $0.6 / 1M tokens
Benchmark Results
Benchmark Category Reasoning Strategy Free Executions Accuracy Cost Duration
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