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Claude 3.7 Sonnet vs Llama 4 Maverick

We don't benchmark Claude 3.7 Sonnet or Llama 4 Maverick on Vision Evals. Claude 3.7 Sonnet is proprietary under Proprietary: commercial use per vendor terms. Llama 4 Maverick is open-weight under Custom.

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AnthropicClaude 3.7 Sonnet

Claude 3.7 Sonnet is deprecated and can no longer be run. Details and evals are still available on its model page.

MetaLlama 4 Maverick
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Claude 3.7 Sonnet vs Llama 4 Maverick Comparison Table

Pricing updated November 1, 2026

PropertyClaude 3.7 SonnetLlama 4 Maverick
OrganizationAnthropicMeta
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateFeb 2024Apr 2025
Context Window200K1.0M
ParametersUnknown400B
LicenseProprietaryCustom
Commercial usecommercial use per vendor termsSee license terms
Pricing per 1M tokens
Input $/1MNo published price$0.188
Output $/1MNo published price$0.652
Vision Tasks
CaptioningSupportedDemo
OCRSupportedDemo
Visual Question AnsweringSupportedDemo
Both support 7 more tasks
Model Features
Both support 3 more features

Claude 3.7 Sonnet vs Llama 4 Maverick: Overview

Claude 3.7 Sonnet

Claude 3.7 Sonnet, released by Anthropic in February 2025, is the company’s first hybrid reasoning model, combining fast response generation with an optional “extended thinking mode” that reveals longer, step-by-step reasoning. Like its predecessors, it is multimodal, handling both text and images, but expands its usability with up to 200,000 input tokens and up to 128,000 output tokens (64K generally available, 128K in beta). This makes it well-suited for analyzing large documents, codebases, or multi-turn conversations.

Typical applications include software development, research workflows, extended reasoning tasks, and enterprise-scale knowledge work where a trade-off between speed and visible reasoning is valuable.

Llama 4 Maverick

Llama 4 Maverick, introduced on April 5, 2025, is one of the first models in Meta’s Llama 4 family, designed as a natively multimodal model supporting text + image inputs with text outputs. It employs a Mixture-of-Experts (MoE) architecture with 128 experts, activating ~17B parameters per token out of a pool of ~400B total parameters. This design improves scalability, efficiency, and reasoning capacity. Maverick has a 1M-token context window, enabling it to handle large documents, extended conversations, and multimodal reasoning. Its knowledge cutoff is August 2024.

The model is released under the Llama 4 Community License and comes in both base and instruction-tuned (“Instruct”) versions. Maverick is widely deployed via Hugging Face, Google Vertex AI, Amazon Bedrock, and Oracle Cloud, making it one of the most accessible large open-weight models. However, it outputs text only (no image/audio generation) and, while input capacity is huge, output limits are typically much smaller. The MoE design also raises hardware demands, as maintaining 128 experts requires significant compute resources, and Meta’s license introduces restrictions around commercial-scale use.