Anthropic's safety-focused flagship versus Meta's open-weight powerhouse. We compare them across eight dimensions to help you choose, then show you how to test both with LLMWise Compare mode.
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| Dimension | Claude Sonnet 4.5 | Llama 4 Maverick | Edge |
|---|---|---|---|
| Coding | Claude Sonnet 4.5 is one of the strongest coding models available, excelling at multi-file refactoring, test generation, and producing clean, idiomatic code with thorough error handling. | Llama 4 Maverick is a capable coder with a growing library of specialized fine-tunes, but it does not match Claude's consistency on complex, production-grade code generation. | |
| Creative Writing | Claude Sonnet 4.5 produces well-structured, thoughtful long-form content with excellent tone consistency, though its style can lean slightly formal. | Llama 4 Maverick generates serviceable creative content but tends toward repetitive phrasing and less nuanced narrative structure on longer outputs. | |
| Math & Reasoning | Claude Sonnet 4.5 demonstrates strong chain-of-thought reasoning and is reliable on graduate-level math, formal logic, and multi-step problem decomposition. | Llama 4 Maverick performs well on standard reasoning benchmarks and benefits from specialized math fine-tunes that can push its performance closer to frontier models. | |
| Speed | Claude Sonnet 4.5 is moderately fast for a frontier model but cannot match the throughput of lighter or speed-optimized alternatives. | Llama 4 Maverick's mixture-of-experts architecture enables fast inference, and optimized serving setups can deliver competitive or faster tokens-per-second than Claude. | |
| Cost | Claude Sonnet 4.5 is a premium-tier model with per-token pricing that adds up quickly for high-volume applications. | Llama 4 Maverick is an order of magnitude cheaper through API providers and effectively free to self-host, making it the clear winner for cost-sensitive workloads. | |
| Context Window | Claude Sonnet 4.5 supports up to 200K tokens and is renowned for maintaining high recall accuracy across the full context length, a major advantage for document-heavy tasks. | Llama 4 Maverick supports a large context window but recall accuracy degrades more noticeably at extreme lengths, especially with aggressive quantization. | |
| Safety | Claude Sonnet 4.5 is the industry leader in safety and alignment, with carefully calibrated refusals, strong system-prompt adherence, and extensive red-teaming behind its guardrails. | Llama 4 Maverick includes Meta's safety training, but being open-weight means guardrails can be removed by end users, making it less suitable for compliance-regulated deployments out of the box. | |
| Customization | Claude Sonnet 4.5 is a closed model with no option to fine-tune or self-host. Customization is limited to prompt engineering and system instructions. | Llama 4 Maverick can be fine-tuned on custom datasets, quantized for hardware constraints, and deployed on-premises with full control over the model stack. |
Claude Sonnet 4.5 is the stronger model on pure quality metrics: coding, reasoning, long-context recall, and safety. Llama 4 Maverick wins on cost, speed, and customization, offering teams the ability to fine-tune and self-host without per-token charges. Choose Claude when output quality and safety are non-negotiable. Choose Llama when you need maximum flexibility and cost control, or when a domain-specific fine-tune can close the quality gap.
Use LLMWise Compare mode to test both models on your own prompts in one API call.
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