Llama 4 Maverick
VerifiedMeta's open multimodal model for long-context text and image tasks.
About Llama 4 Maverick
Llama 4 Maverick features a multimodal architecture that integrates text and image processing. Its context window reaches 1,048,576 tokens, enabling analysis of lengthy inputs. The model is distributed with open weights by Meta.
Strengths include flexible handling of combined visual and textual data over extended sequences. Developers can access and modify the weights for specialized uses. This design promotes experimentation in multimodal scenarios.
Typical usage covers document understanding, visual question answering, and extended conversational agents. Researchers leverage it for projects needing both image interpretation and large-scale text context. The open-weight release facilitates community-driven improvements.
Capabilities
How Llama 4 Maverick compares
Llama 4 Maverick (striped bar) vs other multimodal on intelligence, speed and price.
Price
USD per 1M output tokens · Lower is better · Llama 4 Maverick ranks #27 of 132
Sources: Artificial Analysis (intelligence, speed) · OpenRouter (price).
Best for
Long-context multimodal research
Handles entire research papers or datasets exceeding 500k tokens while interpreting accompanying charts and diagrams in a single pass.
Extended video and audio transcription
Processes hour-long multimodal recordings with synchronized visual and textual elements for detailed summarization or indexing.
Complex visual reasoning over documents
Analyzes lengthy reports containing mixed text, tables, and images to extract insights without chunking or external tools.
Strengths & limitations
Strengths
- +Very large 1M token context window
- +Native multimodal support for text and images
- +Open weights from Meta
- +Strong general reasoning performance
Limitations
- –High compute requirements for full context
- –Limited to text and image modalities
- –Potential for hallucinations on complex tasks
Cost calculator
Estimate what Llama 4 Maverick would cost for your usage.
Based on Llama 4 Maverick's $0.15/1M input · $0.60/1M output. Estimate only — actual cost varies by provider and caching.
Quick start
OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. Only the model slug changes between models.
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://openrouter.ai/api/v1",
apiKey: process.env.OPENROUTER_API_KEY,
});
const completion = await client.chat.completions.create({
model: "meta-llama/llama-4-maverick",
messages: [{ role: "user", content: "Hello!" }],
});
console.log(completion.choices[0].message.content);Model slug: meta-llama/llama-4-maverick
Editor's verdict
Llama 4 Maverick is Meta's open-weight multimodal with a 1049K-token context window.
At $0.60 per 1M output tokens, it is very cost-efficient for its class.
As an open-weight model you can self-host it or call it through a hosted API.
Best suited to very large 1m token context window and native multimodal support for text and images.
Frequently asked questions
The model supports a context length of 1,048,576 tokens as specified in its technical details.
User reviews
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