Comprehensive side-by-side LLM comparison
Claude Opus 4.5 leads with 49.5% higher average benchmark score. Claude Opus 4.5 offers 55.9K more tokens in context window than Claude 3.5 Sonnet. Claude 3.5 Sonnet is $12.00 cheaper per million tokens. Overall, Claude Opus 4.5 is the stronger choice for coding tasks.
Anthropic
Claude 3.5 Sonnet, updated by Anthropic in October 2024 (originally released June 2024), is a large language model from the Claude 3.5 family that delivered strong performance in coding, reasoning, and instruction-following at its release. It supports a 200K token context window, 8K maximum output tokens, and native image understanding including screenshot analysis and document comprehension. Claude 3.5 Sonnet targets general-purpose development tasks, document analysis, and applications requiring reliable instruction following with visual input support.
Anthropic
Claude Opus 4.5, released by Anthropic in November 2025, is a large language model from the Claude 4.5 family built for demanding reasoning tasks, advanced code generation, and complex agentic workflows. It features a 200K token context window, 64K maximum output tokens, native image understanding, and extended thinking with configurable effort levels. Opus 4.5 targets deep analytical work, multi-step tool orchestration, and applications requiring sustained reasoning across long, complex tasks.
1 year newer

Claude 3.5 Sonnet
Anthropic
2024-10-22

Claude Opus 4.5
Anthropic
2025-11-01
Cost per million tokens (USD)
Claude 3.5 Sonnet
Claude Opus 4.5
Context window and performance specifications
Average performance across 2 common benchmarks
Claude 3.5 Sonnet
Claude Opus 4.5
Performance comparison across key benchmark categories
Claude 3.5 Sonnet
Claude Opus 4.5
Claude 3.5 Sonnet
2024-04
Claude Opus 4.5
2025-05
Available providers and their performance metrics
Claude 3.5 Sonnet
Anthropic
AWS Bedrock
Google Cloud Vertex AI
Claude Opus 4.5
Claude 3.5 Sonnet
Claude Opus 4.5
Claude 3.5 Sonnet
Claude Opus 4.5
Anthropic
AWS Bedrock
Google Cloud Vertex AI