Llama 4 Maverick
Pricing updated daily · Last refreshed Oct 30, 2026Meta model with a 524K-token context window, priced at $0.188 per million input tokens and $0.652 per million output tokens.
At a glance
- Provider
- Meta
- Context window
- 524,288 tokens
- Max output
- 16,384 tokens
- Input price
- $0.188 / 1M tokens
- Output price
- $0.652 / 1M tokens
- Input types
- text, image
- Function calling
- Yes
- Released
- April 5, 2025
What it costs
Illustrative request sizes, not measurements of any real product. For your own volumes, use the cost estimator.
| Workload | Tokens in / out | Per request | Per 1,000 requests |
|---|---|---|---|
| Short chat reply | 1,000 / 500 | $0.000514 | $0.5138 |
| Question over retrieved documents | 8,000 / 500 | $0.0018 | $1.83 |
| Summarise a long document | 50,000 / 1,500 | $0.0104 | $10.35 |
How it compares
- Input price ($0.188 per 1M tokens) is the 10th lowest of 30 models in the catalogue.
- Output price ($0.652 per 1M tokens) is the 11th lowest of 30.
- Context window (524K tokens) is the 17th largest of 30.
- Maximum output (16K tokens) is the 23rd largest of 30.
- On blended price it is 96% more expensive than the median Meta model in the catalogue.
These are rankings by listed price and size within this catalogue (blended price weights input 3:1 against output), not a measure of output quality.
Cheaper models with the same capabilities
Lower blended price, at least the same context window, and the same input types and function calling.
| Model | Provider | Context | Input $/1M | Output $/1M |
|---|---|---|---|---|
| Llama 4 Scout | Meta | 1.31M | $0.10 | $0.30 |
| Claude Haiku 5.5 | Anthropic | 1M | $0.10 | $0.50 |
| GPT-6 Luna Pro | OpenAI | 1.05M | $0.10 | $0.50 |
More from Meta
| Model | Provider | Context | Input $/1M | Output $/1M |
|---|---|---|---|---|
| Llama Guard 4 12B | Meta | 164K | $0.18 | $0.18 |
| Llama 4 Scout | Meta | 1.31M | $0.10 | $0.30 |
| Llama 3.3 70B Instruct | Meta | 131K | $0.10 | $0.32 |
| Llama 3.2 1B Instruct | Meta | 60K | $0.027 | $0.201 |
Try it with your own text
- Token counter: see how many tokens a prompt uses (exact for OpenAI models, labelled estimates for others).
- Context window visualizer: see how much of this model’s 524K window a prompt fills.
- Model comparison: sort and filter every model, and export to CSV.
Source: OpenRouter’s public model catalogue (meta-llama/llama-4-maverick), read once a day. These are the prices OpenRouter charges; a provider’s own list price can differ, so check the provider before committing to a budget.