Meta: Llama 4 Maverick✓ Catalog verified
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.
Overview
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.
Access: available through the official Meta API. Context window: 1.0M.
Specifications
| API identifier | meta-llama/llama-4-maverick |
| Provider | Meta |
| Model type | Multimodal LLM |
| Context window | 1.0M catalog |
| Input modalities | text · image |
| Output modalities | text |
| Released | Apr 5, 2025 |
| Tokenizer | Llama4 |
| Moderated | No |
| Architecture modality | text+image->text |
Pricing
Live pricing components for meta-llama/llama-4-maverick as published in the catalog.
| Pricing component | Raw unit price | Normalized | Unit |
|---|---|---|---|
| Prompt tokens | $1.5e-7 | $0.15 / 1M | Per input token |
| Completion tokens | $6e-7 | $0.60 / 1M | Per output token |
| Request fee | N/A | N/A | Per request |
| Image fee | N/A | N/A | Per image unit |
| Web search fee | N/A | N/A | Per search request |
Cost calculator
Estimate monthly spend from your own token volumes.
Estimated Total Cost
$0.2Calculated from current list pricing in the ModelsAtlas catalog.Capabilities
| Capability | Status | What it means |
|---|---|---|
| Visual Understanding | ✓ Supported | Image and document analysis support |
| Audio Processing | Not advertised | Speech and voice aligned flows |
| Tool Calling | ✓ Supported | Supports tools / function calling |
| Self-Hosting | ✓ Supported | Deploy outside managed APIs |
Capability signals
Directional signals derived from model metadata and capability tags — not official benchmark submissions.
Quick start
Call Meta: Llama 4 Maverick through an OpenAI-compatible client.
from openai import OpenAI
client = OpenAI(
base_url="https://openrouter.ai/api/v1",
api_key="YOUR_API_KEY"
)
response = client.chat.completions.create(
model="meta-llama/llama-4-maverick",
messages=[{"role": "user", "content": "Explain quantum physics."}]
)
print(response.choices[0].message.content)Alternatives
Closest models by context window from a different provider.
| Model | Provider | Context | Input /1M | Actions |
|---|---|---|---|---|
| Google: Gemini 2.0 Flash | 1.0M | $0.10 | View → | |
| Google: Gemini 2.0 Flash Lite | 1.0M | $0.07 | View → |
Sources & attribution
Pricing and metadata are maintained in the ModelsAtlas catalog.
Frequently asked questions
How much does Meta: Llama 4 Maverick cost?
$0.15 per 1M input tokens and $0.60 per 1M output tokens on the official Meta API.
What is the context window of Meta: Llama 4 Maverick?
Meta: Llama 4 Maverick supports up to 1.0M tokens of context.
Does Meta: Llama 4 Maverick support tool / function calling?
Yes, Meta: Llama 4 Maverick supports tool / function calling — you can register tools and the model will emit structured tool calls.
How do I access Meta: Llama 4 Maverick?
Use the official Meta API with the model id `meta-llama/llama-4-maverick`. See the Quick start section above for code examples.