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Llama 4 Maverick

by Meta

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

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Llama 4 Maverick

Added 10 July 2026

#meta-llama

Overview

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...

Best for

Best for
Teams that want open-weight flexibility with hosted convenience

Use cases

  • self-host experiments
  • cost-controlled apps
  • fine-tune pipelines

How to use / API access

Call via OpenRouter with model id `meta-llama/llama-4-maverick`.

  • openrouter · meta-llama/llama-4-maverick Docs

OpenRouter id: meta-llama/llama-4-maverick

Benchmarks

  • Intelligence Index (artificial-analysis) : 14.3 index
  • Coding Index (artificial-analysis) : 16.3 index
  • Agentic Index (artificial-analysis) : 1.3 index
  • Design Arena 3d (other) : 974 elo · #93
  • Design Arena codecategories (other) : 923 elo · #104
  • Design Arena dataviz (other) : 924 elo · #102
  • Design Arena gamedev (other) : 903 elo · #104

Enterprise DNA angle

EDNA helps teams decide when open weights belong in Omni vs when a closed frontier model is cheaper in total cost of quality.

Notes

Llama 4 Maverick is listed in the EDNA Models directory from the OpenRouter catalogue.

Pros

  • Open-weights family economics
  • Strong community and self-host path

Cons

  • Hosted quality depends on the OpenRouter endpoint
  • May trail closed frontier models on hardest tasks
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