LLM ComparisonClaude 4.5 SonnetClaude 4.6 Opus

Claude 4.5 Sonnet vs Claude 4.6 Opus

Compare Claude 4.5 Sonnet and Claude 4.6 Opus. Build AI products powered by either model on Appaca.

Model Comparison

FeatureClaude 4.5 SonnetClaude 4.6 Opus
ProviderAnthropicAnthropic
Model Typetexttext
Context Window1,000,000 tokens1,000,000 tokens
Input Cost
$3.00/ 1M tokens
$5.00/ 1M tokens
Output Cost
$15.00/ 1M tokens
$25.00/ 1M tokens

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Strengths & Best Use Cases

Claude 4.5 Sonnet

Anthropic

1. Best-in-class coding performance

  • #1 on SWE-bench Verified (77.2% standard, 82.0% high-compute).
  • Excels at debugging, architecture, and multi-file code generation.
  • Maintains coherence for extremely long tasks (30+ hours).

2. State-of-the-art computer use & agents

  • Leads OSWorld at 61.4%.
  • Strongest model for agentic workflows, multi-step tool use, and real computer control.
  • Powering Claude Code, the new Claude Agent SDK, and Chrome agent actions.

3. Advanced reasoning & math

  • Large improvements across reasoning-heavy benchmarks (AIME, MMMLU, τ2-bench, Terminal-Bench).
  • Deep multi-step reasoning with extended or interleaved thinking.

4. High alignment & safety

  • Most aligned Claude model to date with reduced deception, hallucinations, sycophancy, and harmful compliance.
  • Strong protections against prompt injection for agentic tasks (ASL-3 safeguards).

5. Domain-expert performance

  • Notable gains in finance, law, medicine, and STEM tasks.
  • Trusted by early customers for long-context legal analysis, multi-file engineering, security research, and red-teaming.

Claude 4.6 Opus

Anthropic

1. Anthropic's top model for coding and agents

  • Anthropic positions Opus 4.6 as its most intelligent model for building agents and coding.
  • It builds on Opus 4.5 with higher reliability and precision for professional software engineering, complex agentic workflows, and high-stakes enterprise tasks.

2. Strong frontier performance on real agent benchmarks

  • Anthropic reports state-of-the-art results across coding and agentic evaluations.
  • Public benchmark highlights include 65.4% on Terminal-Bench 2.0, 72.7% on OSWorld, and 90.2% on BigLaw Bench.

3. Best fit for long-horizon, high-context work

  • Supports up to a 1M token context window in beta and up to 128K output tokens.
  • Designed for long-running tasks that need sustained planning, careful debugging, code review, and strong context retention.

4. Advanced reasoning controls and workflow support

  • Supports adaptive thinking and the effort parameter, including the new max effort level.
  • Anthropic also introduced fast mode, compaction, and dynamic filtering with web search and web fetch for Opus 4.6-era agent workflows.

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