LLM AtlasLLM AtlasSearch models

Meta

Llama 4 Maverick

Overall 84Open weightopen-weight

Meta's 17Bx128E MoE open-weight model with 1M token context, pretrained on ~22T tokens. Strong multimodal and multilingual capabilities for teams that need control, private deployment, and customization.

Last verified: 2026-03-29Confidence: HighSources: 3
textvisionopen-sourcecode
Input price
$0.0008/1K tok
Output price
$0.002/1K tok
Context window
1,048,576
Max output
65,536
Release date
2025-04-05
Access
open-weight, self-hosted, hosted
License
Llama 4 Community License
Last verified
2026-03-29

Capability profile

Radar view of the model's practical strengths. This chart is backed by textual summaries below for crawlability.

Benchmark summary

A notable open-weight flagship with strong economics and adaptable deployment paths, scoring 80.5 on MMLU-Pro and 69.8 on GPQA Diamond.

Strengths

  • Open-weight flexibility
  • Fine-tuning friendliness
  • Low effective serving cost
  • 1M token context window

Trade-offs

  • Safety guardrails vary by deployment
  • More integration work required

Crawlable benchmark analysis

Llama 4 Maverick is positioned as an open-weight generalist model with published scores that emphasize its practical fit for buyers evaluating the entry.

Published scores highlight reasoning 84/100, coding 82/100, enterprise readiness 78/100, vision 79/100, speed 87/100, and safety 76/100.

Pricing is not applicable for this self-hosted or open-weight entry. With a context window of 1,048,576 tokens, it supports large-document analysis and retrieval workflows.

Across the tracked benchmark set, Llama 4 Maverick shows especially strong performance in ARC-Challenge, making it a viable option for teams prioritizing reasoning-heavy use cases.

Sources

Provider and distribution links used to verify this model record.

Last verified: 2026-03-29

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