Claude 3.5 Sonnet vs Llama 4 Maverick
How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for Claude 3.5 Sonnet and Llama 4 Maverick.
Claude 3.5 Sonnet
Claude 3.5 Sonnet was Anthropic's breakout model of 2024, widely regarded as one of the most capable commercial LLMs of its generation. It earned widespread developer praise for its exceptional coding ability, nuanced long-form writing, and reliable complex reasoning across a 200,000-token context window. Claude 3.5 Sonnet introduced computer-use capabilities, enabling it to interact with desktop environments, web browsers, and software tools autonomously. Available via API at $3/MTok for input, it continues to be a popular choice for developers who want a well-rounded, safety-aligned model with strong benchmark performance for coding, analysis, and content generation tasks.
Llama 4 Maverick
Meta's next-generation open weights model. Delivers premium agentic capabilities, reasoning, and tool call compliance for local or self-hosted enterprise stacks.
Technical Specifications
| Specification | Claude 3.5 Sonnet | Llama 4 Maverick |
|---|---|---|
| Provider | Anthropic | Meta |
| Context Window | 200,000 tokens | 1,048,576 tokens |
| Agent Suitability | N/A | 89/100 |
| Time to First Token (TTFT) | N/A | 300 ms |
| Deployment Model | N/A | self hostable |
| Production Stability | stable | stable |
| API Available | Yes | Yes |
| Released Date | 2024-06-21 | 2026-05-25 |
API Pricing Comparison
Input Price per Million Tokens
Claude 3.5 Sonnet
$3.00
Llama 4 Maverick
$0.15
Output Price per Million Tokens
Claude 3.5 Sonnet
$15.00
Llama 4 Maverick
$0.60
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Benchmark Performance Metrics
Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.
Claude 3.5 Sonnet Quirks & Gotchas
No developer gotchas reported.
Llama 4 Maverick Quirks & Gotchas
- ▸Self-hostable via Ollama/Docker — ideal for on-premise deployments
- ▸Requires specific system prompt for optimal function calling reliability