Best for long context
Large context window for documents and transcripts.
Model · Meta
Meta Llama 4 Maverick
Meta Llama 4 Maverick is served by Meta through OpenRouter. It provides 1.05M tokens of context and supports text, vision inputs.
Context window
1.05M tokens
Input / 1M tokens
$0.188
Output / 1M tokens
$0.652
Key facts
| Provider | Meta |
| OpenRouter ID | meta-llama/llama-4-maverick |
| Modalities | Text, Vision |
| Best for | Budget, Long Context, Multimodal |
Source
openrouter.ai/api/v1/models Verified 2026-10-16 Drift-checked daily 06:00 CST Best-fit workloads
Best for budget
Low input/output cost for high-volume workloads.
Best multimodal
Handles images, files, audio or video inputs.
Cost estimates
These examples use the 2026-10-16 input and output prices. Cache discounts, provider surcharges and tool fees are excluded.
| Workload | Input | Output | Estimated cost |
|---|---|---|---|
| Quick test | 20,000 | 5,000 | $0.007 |
| Product chat month | 500,000 | 125,000 | $0.175 |
| Document batch | 5,000,000 | 1,000,000 | $1.59 |
Strengths
- ✓ Low-cost open-weight family
- ✓ Good default for self-hostable or flexible deployments
- ✓ Large context window
Limitations
- ! Not as strong as frontier proprietary models
- ! Open-weight behavior varies by hosted provider
OpenRouter API quickstart
Run these examples from your server or edge function. Keep the OpenRouter API key private and do not expose it in browser code.
cURL
curl https://openrouter.ai/api/v1/chat/completions \
-H "Authorization: Bearer $OPENROUTER_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "meta-llama/llama-4-maverick",
"messages": [{ "role": "user", "content": "Summarize this document in five bullet points." }],
"max_tokens": 500
}'JavaScript / TypeScript
const response = await fetch("https://openrouter.ai/api/v1/chat/completions", {
method: "POST",
headers: {
Authorization: `Bearer ${process.env.OPENROUTER_API_KEY}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
model: "meta-llama/llama-4-maverick",
messages: [{ role: "user", content: "Summarize this document in five bullet points." }],
max_tokens: 500,
}),
});
const data = await response.json();
console.log(data.choices[0].message.content);How to evaluate Meta Llama 4 Maverick
- Run five real tasks from your product, not generic demo prompts.
- Record token usage, latency and output quality.
- Estimate cost using your real input/output mix.
- Compare it against one model with a similar price and one stronger model.
Compare models View on OpenRouter ↗
Meta Llama 4 Maverick FAQ
What is Meta Llama 4 Maverick?
Meta Llama 4 Maverick is a Meta model available through OpenRouter. It supports text, vision inputs and is suited for budget, long context, multimodal workloads.
How much does Meta Llama 4 Maverick cost on OpenRouter?
The 2026-10-16 snapshot lists $0.188 per 1M input tokens and $0.652 per 1M output tokens. Verify current pricing on OpenRouter before production.
How large is Meta Llama 4 Maverick's context window?
Meta Llama 4 Maverick offers 1.05M tokens of context in the current snapshot. Provider-specific limits and surcharges may apply.
Head-to-head comparisons
Meta Llama 4 Maverick vs DeepSeek V4 Flash
Llama 4 Maverick is the better low-cost choice when image input matters. DeepSeek V4 Flash is the better pure-text batch choice when output cost dominates.
Pricing and context data are based on a 2026-10-16 snapshot. Provider limits can change; always verify on OpenRouter before production.