Meta: llama-4-maverick-17b-128e-instruct:free

llama-4-maverick-17b-128e-instruct:free
128K context8.2K outToolsVisionStructured
Released Apr 5, 2025Knowledge cutoff 2024Updated Apr 5, 2025

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.

Mode chatTokenizer Llama4Quantization fp8meta-llama/Llama-4-Maverick-17B-128E-Instruct

Pricing

Input price
$0.00/ 1M tokens
Output price
$0.00/ 1M tokens
Context window 128K tokensCompatible endpoints openaiVendor Meta

Performance

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Usage & Ranking

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Supported parameters

All providers = every upstream serving this model supports it. Some providers = depends on which upstream handles the request. Default = the value sent when you leave the parameter unset.

ParameterProvidersDefault
frequency_penaltySome providers-
logit_biasSome providers-
logprobsSome providers-
max_tokensAll providers-
min_pSome providers-
presence_penaltySome providers-
repetition_penaltySome providers-
response_formatAll providers-
seedSome providers-
stopSome providers-
structured_outputsAll providers-
temperatureAll providers-
tool_choiceSome providers-
toolsSome providers-
top_kSome providers-
top_logprobsSome providers-
top_pAll providers-

Frequently asked questions

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