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Llama 4 MaverickvsClaude Opus 4

Meta vs Anthropic — Side-by-side model comparison

Llama 4 Maverick leads 4/5 categories

Head-to-Head Comparison

MetricLlama 4 MaverickClaude Opus 4
Provider
Meta
Arena Rank
#7
#1
Context Window
1M
200K
Input Pricing
Free/1M tokens
$5.00/1M tokens
Output Pricing
Free/1M tokens
$25.00/1M tokens
Parameters
400B MoE (17B active)
Undisclosed
Open Source
Yes
No
Best For
Open source, self-hosted, multilingual
Complex reasoning, coding, agentic tasks
Release Date
Apr 5, 2025
May 22, 2025

Llama 4 Maverick

Llama 4 Maverick, developed by Meta AI, is a large Mixture-of-Experts model representing the most capable freely available AI for general-purpose tasks. As Meta's flagship open-source release, Maverick demonstrates strong performance across coding, reasoning, creative writing, and multilingual tasks, competing with proprietary models on standard benchmarks. The MoE architecture activates only a subset of its total parameters per token, enabling frontier-class capability with manageable inference costs. It can be downloaded, modified, fine-tuned, and deployed without API costs or licensing restrictions. The model has become a foundation for thousands of fine-tuned variants across the open-source community, powering applications in healthcare, education, content creation, and enterprise software. Llama 4 Maverick reflects Meta's strategic investment in open-source AI, building developer ecosystem engagement while advancing the accessibility of powerful AI models globally.

Claude Opus 4

Claude Opus 4 is Anthropic's most powerful AI model, holding the #1 position on the Chatbot Arena leaderboard. It represents a breakthrough in extended thinking and agentic capabilities, able to work autonomously on complex multi-step tasks for hours. With a 200K token context window, it excels at analyzing entire codebases, lengthy legal documents, and research papers in a single pass. The model demonstrates exceptional performance in coding (setting new benchmarks on SWE-bench), advanced reasoning, and nuanced writing tasks. Its agentic capabilities allow it to use tools, navigate computers, and execute multi-step workflows with minimal human oversight. Opus 4 is the preferred choice for enterprises requiring the highest quality output on mission-critical tasks where accuracy and depth matter more than speed or cost.

View Anthropic profile →

Key Differences: Llama 4 Maverick vs Claude Opus 4

1

Claude Opus 4 ranks higher in arena benchmarks (#1) indicating stronger overall performance.

2

Llama 4 Maverick supports a larger context window (1M), allowing it to process longer documents in a single request.

3

Llama 4 Maverick is open-source (free to self-host and fine-tune) while Claude Opus 4 is proprietary (API-only access).

L

When to use Llama 4 Maverick

  • +Budget is a concern and you need cost efficiency
  • +You need to process long documents (1M context)
  • +You need to self-host or fine-tune the model
  • +Your use case involves open source, self-hosted, multilingual
View full Llama 4 Maverick specs →
C

When to use Claude Opus 4

  • +You need the highest quality output based on arena rankings
  • +Quality matters more than cost
  • +You prefer a managed API without infrastructure overhead
  • +Your use case involves complex reasoning, coding, agentic tasks
View full Claude Opus 4 specs →

Cost Analysis

At current pricing, Llama 4 Maverick is nullx more affordable than Claude Opus 4. For a typical enterprise workload processing 100M tokens per month:

Llama 4 Maverick monthly cost

$0

100M tokens/mo (50/50 in/out)

Claude Opus 4 monthly cost

$1,500

100M tokens/mo (50/50 in/out)

The Verdict

Llama 4 Maverick wins our head-to-head comparison with 4 out of 5 category wins. It's the stronger choice for open source, self-hosted, multilingual, though Claude Opus 4 holds an edge in complex reasoning, coding, agentic tasks.

Last compared: April 2026 · Data sourced from public benchmarks and official pricing pages

Frequently Asked Questions

Which is better, Llama 4 Maverick or Claude Opus 4?
In our head-to-head comparison, Llama 4 Maverick leads in 4 out of 5 categories (arena rank, context window, input pricing, output pricing, and parameters). Llama 4 Maverick excels at open source, self-hosted, multilingual, while Claude Opus 4 is better suited for complex reasoning, coding, agentic tasks. The best choice depends on your specific requirements, budget, and use case.
How does Llama 4 Maverick pricing compare to Claude Opus 4?
Llama 4 Maverick charges Free per 1M input tokens and Free per 1M output tokens. Claude Opus 4 charges $5.00 per 1M input tokens and $25.00 per 1M output tokens. Llama 4 Maverick is the more affordable option. For high-volume production workloads, the pricing difference can significantly impact total cost of ownership.
What is the context window difference between Llama 4 Maverick and Claude Opus 4?
Llama 4 Maverick supports a 1M token context window, while Claude Opus 4 supports 200K tokens. Llama 4 Maverick can process longer documents, codebases, and conversations in a single request. Context window size matters most for tasks involving long documents, large codebases, or extended conversations.
Can I use Llama 4 Maverick or Claude Opus 4 for free?
Llama 4 Maverick is available for free (open-source). Claude Opus 4 is a paid API model starting at $5.00 per 1M input tokens. Open-source models can be self-hosted for free but require your own GPU infrastructure.
Which model has better benchmarks, Llama 4 Maverick or Claude Opus 4?
Llama 4 Maverick holds arena rank #7, while Claude Opus 4 holds rank #1. Claude Opus 4 performs better in overall arena benchmarks, which aggregate human preference ratings across coding, reasoning, and general tasks. Note that benchmarks don't capture every use case — we recommend testing both models on your specific tasks.
Is Llama 4 Maverick or Claude Opus 4 better for coding?
Llama 4 Maverick's primary strength is open source, self-hosted, multilingual. Claude Opus 4 is specifically optimized for coding tasks. For coding specifically, arena rank and code-specific benchmarks are the best indicators of performance.