Llama 4 Maverick
meta/llama-4-maverickОт Meta · семейство: llama · выпуск 2025-04-05 · дата знаний: 2024-08
Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.
Возможности
Model fit scores
0–100 · higher is betterThese scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.
Coding87
- Tool calling40/40
- Structured output20/20
- Reasoning0/10
- Context window (100K → 1M)20/20
- Provider availability7/10
Agents77
- Tool calling35/35
- Structured output25/25
- Reasoning0/15
- Output token limit10/15
- Provider availability7/10
JSON / structured output99
- Structured output / JSON mode50/50
- Tool calling20/20
- Temperature control10/10
- Price-friendly for high-volume19/20
Cost efficiency71
- Headline price (log-scaled)66/95
- Has prompt-cache pricing5/5
Long context91
- Context window (100K → 2M)81/90
- Has published price for full window10/10
Vision97
- Accepts image input50/50
- Context window (10K → 1M)30/30
- Has published price10/10
- Provider availability7/10
Production-readiness91
- Number of independent providers35/40
- Has published per-token price20/20
- Context window ≥ 8K15/15
- No data inconsistencies across providers6/10
- Official model (not derivative)15/15
Cost Efficiency Index
Open full calculator →Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.
| Scenario | Cost | Assumption |
|---|---|---|
RAG answer per 1,000 RAG answers | $0.92 < $0.01 per request | 5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot. |
Support ticket triage per 10,000 tickets | $1.84 < $0.01 per request | 1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support. |
Data extraction per 1,000 documents | $0.55 < $0.01 per request | 2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines. |
Code review per 1,000 PRs | $1.59 < $0.01 per request | 8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads. |
Agent step per 1,000 steps | $1.85 < $0.01 per request | 12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step. |
Детализация цен
Рекомендованная цена от cortecs · llama-4-maverick
Самый дешёвый провайдер: vercel · Unknown вход + Unknown выход
Доступна у 7 провайдеров
| Провайдер | ID модели провайдера | Вход / 1M | Выход / 1M | Контекст | Выпуск |
|---|---|---|---|---|---|
| OpenRouter openrouter | meta-llama/llama-4-maverick | $0.150 | $0.600 | 1.05M | 2025-04-05 |
| Vercel AI Gateway vercel | meta/llama-4-maverick | Unknown | Unknown | 128K | 2025-04-05 |
| Cortecs cortecs | llama-4-maverick | $0.124 | $0.603 | 1M | 2025-04-05 |
| DigitalOcean digitalocean | llama-4-maverick | $0.250 | $0.870 | 1M | 2025-04-05 |
| Helicone helicone | llama-4-maverick | $0.150 | $0.600 | 131K | 2025-01-01 |
| Kilo Gateway kilo | meta-llama/llama-4-maverick | $0.150 | $0.600 | 1.05M | 2025-04-05 |
| NanoGPT nano-gpt | meta-llama/llama-4-maverick | $0.180 | $0.800 | 1.05M | 2025-09-05 |
Расхождения данных между провайдерами
- context_window varies: 1000000, 1048576, 128000, 131072
- release_date varies (span 247d): 2025-01-01, 2025-04-05, 2025-09-05
Провайдеры сообщают разные значения для этой модели. Сводка выше использует репрезентативного провайдера; детали — в таблице.
Frequently asked questions
How much does Llama 4 Maverick cost?
Llama 4 Maverick costs $0.124 per 1M input tokens and $0.603 per 1M output tokens, sourced from cortecs. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.
What is the context window of Llama 4 Maverick?
Llama 4 Maverick has a context window of 1.05M tokens, with a max output of 16K tokens per reply. This is the total combined size of prompt + completion.
Does Llama 4 Maverick support tool calling?
Yes. Llama 4 Maverick supports tool calling (function calling). This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.
Does Llama 4 Maverick support structured output / JSON mode?
Yes. Llama 4 Maverick supports structured output / JSON-schema-constrained decoding. This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.
Can Llama 4 Maverick accept image input?
Yes. Llama 4 Maverick accepts both text and image input. Vision pricing per image is usually billed on top of the regular token rate — check Meta's docs for the exact rule.
Is Llama 4 Maverick open-weight?
Yes. Llama 4 Maverick's weights are publicly available, so you can self-host or fine-tune. Note that open weights ≠ open source — the training data and code are typically not released.
What are the best alternatives to Llama 4 Maverick?
If Llama 4 Maverick doesn't fit, consider Llama-3.3-70B-Instruct, Meta-Llama-3.1-8B-Instruct, Llama 4 Scout 17B 16E Instruct. Each one targets the same use case — see the Related links below for direct head-to-head pages.
Where does this data come from?
All numbers are normalised into a single canonical model record and reconciled with each provider's official documentation. We re-pull daily and write any changes (price, context, capability) to the /changelog page.
Explore more
More Meta models
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- Meta-Llama-3.1-8B-Instruct$0.02 in / $0.03 out
- Llama 4 Scout 17B 16E Instruct$0.10 in / $0.30 out
- Llama 4 Maverick 17B 128E Instruct FP8$0.14 in / $0.59 out
- Meta-Llama-3-8B-Instruct$0.03 in / $0.04 out
Capability lists this model is in
Последнее обновление:
Pricing and capabilities are refreshed daily and reconciled against each provider's official documentation. Always verify critical production decisions with the provider directly.