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Llama 4 Maverick

Access Llama 4 Maverick through one API key. Meta's most capable open-weight model.

Meta's larger open-weight model. More capable than Scout with a massive 1M context window.

No credit card required. Takes 30 seconds.

2,400+

Developers

1.2M+

API calls served

100+

Endpoints

$0.01

Per call

Yep, that's it.

Try it live

Send a message and see Llama 4 Maverick respond in real time.

POST/v1/ai/chat

Maximum tokens in the response.

Real-time tokens

Hit "Send Request" to see the response

Context Window

1.0M tokens

Max Output

16K tokens

Input Price

$0.22 / 1M tokens

Output Price

$0.89 / 1M tokens

Strengths

✓
Open-weight

Meta releases Llama 4 Maverick with open weights, so teams can validate behavior against a published model and avoid lock-in to a single closed system.

✓
1M context

A 1,048,576-token context window lets Maverick process very large documents, codebases, or conversation histories in one request, with up to 16,384 output tokens.

✓
Stronger than Scout

Maverick is the more capable of Meta's Llama 4 pair, outperforming the smaller Scout on reasoning and general tasks while keeping open weights.

✓
Competitive pricing

At $0.22 per 1M input and $0.89 per 1M output tokens, it delivers frontier-scale context and open-weight flexibility at a low price point.

Quick start

Copy this snippet and start making calls with Llama 4 Maverick.

const res = await fetch('https://api.yepapi.com/v1/ai/chat', {
  method: 'POST',
  headers: {
    'x-api-key': 'YOUR_API_KEY',
    'Content-Type': 'application/json',
  },
  body: JSON.stringify({
    "model": "meta-llama/llama-4-maverick",
    "messages": [
      {
        "role": "user",
        "content": "Explain API gateways in 2 sentences."
      }
    ],
    "maxTokens": 256
  }),
});
const { data } = await res.json();
console.log(data.message.content);

Why use Llama 4 Maverick through YepAPI?

✓One API key for all models — no separate accounts
✓OpenAI SDK compatible — just change the base URL
✓No monthly minimums — pay per token
✓Switch models with one line of code
✓Full provider passthrough — citations, search results, and all extras included
✓Streaming and non-streaming support on every model
✓Works with Cursor, Claude, LangChain, and any LLM tool
✓Unified billing across all providers

Llama 4 Maverick API: Meta's capable open-weight model with 1M context

Llama 4 Maverick is the larger and more capable model in Meta's Llama 4 release, an open-weight model with a million-token context window aimed at teams that want capability without closed-system lock-in.

Through YepAPI you access Llama 4 Maverick on one OpenAI-compatible endpoint at $0.22 per 1M input and $0.89 per 1M output tokens, with a 1,048,576-token context window.

What is Llama 4 Maverick?

Llama 4 Maverick is Meta's higher-tier Llama 4 model, sitting above the smaller Llama 4 Scout in capability. As an open-weight model, its parameters are published, which appeals to teams that value transparency, the option to self-host, and freedom from dependence on any single closed provider. Maverick pairs that openness with a 1,048,576-token context window and up to 16,384 output tokens, letting it reason over very large inputs. It is positioned as a general-purpose model strong on reasoning, instruction following, and coding, making it a flexible default for builders who prefer the open Llama ecosystem.

Build with Llama 4 Maverick via YepAPI

Call Llama 4 Maverick through YepAPI's OpenAI-compatible /v1/ai/chat endpoint. Point your OpenAI SDK at YepAPI, set the model string to llama-maverick, and you are running Meta's open-weight model; switching to any other model later is a single-string edit. One YepAPI key also covers every other model plus SEO, SERP, and web-scraping tools, so you can prototype on Maverick and route specific tasks elsewhere without changing providers or keys.

Llama 4 Maverick API pricing — $0.22 / $0.89 per 1M tokens

Llama 4 Maverick costs $0.22 per 1M input tokens and $0.89 per 1M output tokens on YepAPI. That pricing is notable given the million-token context and open-weight pedigree: it lets you feed very large inputs affordably while keeping the option to compare against a publicly available model. For long-context summarization and analysis, the low input rate keeps the dominant cost manageable at scale.

Llama 4 Maverick for open-weight, long-context builds

Maverick suits teams that want a capable, transparent model for long-context work: analyzing large documents or entire codebases, multi-turn assistants with long histories, and general reasoning where the published weights aid evaluation and reduce lock-in risk. It is also a sensible benchmark, since its open nature makes its behavior easier to study. The 1M window means heavy chunking is rarely needed for large inputs.

Try Llama 4 Maverick free

New YepAPI accounts include $5 of free credit with no card required. That covers testing Llama 4 Maverick's million-token context on your real workloads and comparing it head-to-head with other models before you commit.

Start generating in 30 seconds

$5 free credit on signup. No credit card required. Pay per call.

What developers say

“Switched from SerpAPI and cut our SERP costs by 80%. Same data quality, way simpler billing.”

Marcus T.

SEO Platform Founder

“One API key for AI models, SERP data, and web scraping. Saved us from managing 4 separate providers.”

Priya S.

Full-Stack Developer

“The $5 free credit let us prototype our entire rank tracking feature before committing. No other API does that.”

Jake R.

Indie Hacker

Frequently asked questions

Meta's larger open-weight model. More capable than Scout with a massive 1M context window.

Input tokens cost $0.22 per 1M tokens and output tokens cost $0.89 per 1M tokens through YepAPI. No monthly minimums — you only pay for what you use.

Sign up for a free API key, then send requests to the /v1/ai/chat endpoint.

Llama 4 Maverick supports a 1.0M token context window with up to 16K output tokens per request.

Ready to use Llama 4 Maverick?

$5 free credit on signup. No credit card required. Pay per call.

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