LLM Comparison
Llama 4 Maverick vs Claude Opus 4.7
Side-by-side specs, pricing & capabilities · Updated May 2026
Price vs Intelligence
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2/6 modelsSame tier:
| Organization | ||
| OpenTools Score | 38 101 | 71 4.7 |
| Family | Llama | Claude |
| Status | Current | Current |
| Release Date | Apr 2025 | Apr 2026 |
| Context Window | 1.0M tokens | 1.0M tokens |
| Input Price | $0.15/M tokens | $5.00/M tokens |
| Output Price | $0.60/M tokens | $25.00/M tokens |
| Pricing Notes | — | Cache read: $0.5000/M tokens |
| Capabilities | textvisioncode | textvisioncodetool-use |
| Max Output | 16K tokens | 128K tokens |
| API Identifier | meta-llama/llama-4-maverick | anthropic/claude-opus-4.7 |
| Benchmarks | ||
| MMLU | 85.5meta | 84.7anthropic |
| MMLU Pro | 80.5meta | — |
| GPQA | 69.8meta | — |
| MATH | 61.2meta | — |
| LiveCodeBench | 43.4meta | — |
| MMMU | 73.4meta | — |
| MMLU-Pro | — | 78.1anthropic |
| MMMLU | — | 92anthropic |
| GPQA Diamond | — | 94.2anthropic |
| HLE | — | 54.7artificial-analysis |
| SWE-bench Verified | — | 87.6anthropic |
| SWE-bench Pro | — | 64.3anthropic |
| SWE-bench Multilingual+Multimodal | — | 80.5anthropic |
| Terminal-Bench | — | 69.4anthropic |
| MCP-Atlas | — | 77.3anthropic |
| Berkeley Function Calling | — | 77.3anthropic |
| OSWorld-Verified | — | 78anthropic |
| BrowseComp | — | 79.3anthropic |
| CharXiv-R | — | 91anthropic |
| DocVQA | — | 93.1anthropic |
| CyberGym | — | 73.1anthropic |
| GDPVal-AA Elo | — | 1753artificial-analysis |
| View Llama 4 Maverick | View Claude Opus 4.7 | |
Cost Calculator
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| Model | Input | Output | Total / mo | vs Best |
|---|---|---|---|---|
| Llama 4 MaverickCheapest | $0.15 | $0.30 | $0.45 | — |
| Claude Opus 4.7 | $5.00 | $12.50 | $17.50 | +3789% |
Meta
Llama 4 Maverick
Llama 4 Maverick is a multimodal llm from Meta. Supports up to 1,048,576 token context window. Achieves 88.4% on MMLU. Available from $0.15/M input tokens.
Anthropic
Claude Opus 4.7
Claude Opus 4.7 is Anthropic's most capable generally available model, with significant improvements in advanced software engineering, agentic tool use, and vision resolution. Achieves 87.6% on SWE-bench Verified and 94.2% on GPQA Diamond. Supports up to 1,000,000 token context window with 3.3x higher-resolution vision than Opus 4.6.
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