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LLM ComparisonClaude 4.7 OpusClaude 4.5 Sonnet

Claude 4.7 Opus vs Claude 4.5 Sonnet

Compare Claude 4.7 Opus and Claude 4.5 Sonnet. Build AI products powered by either model on Appaca.

Model Comparison

FeatureClaude 4.7 OpusClaude 4.5 Sonnet
ProviderAnthropicAnthropic
Model Typetexttext
Context Window1,000,000 tokens1,000,000 tokens
Input Cost
$5.00/ 1M tokens
$3.00/ 1M tokens
Output Cost
$25.00/ 1M tokens
$15.00/ 1M tokens

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Strengths & Best Use Cases

Claude 4.7 Opus

Anthropic

1. State-of-the-art software engineering

  • A notable upgrade over Opus 4.6 on the hardest coding tasks, with users reporting they can hand off work that previously required close supervision.
  • Early partners reported double-digit gains on real-world benchmarks — e.g., Cursor saw CursorBench jump from 58% to 70%, and Rakuten-SWE-Bench resolution tripled versus Opus 4.6.
  • Handles complex, long-running tasks with rigor: plans carefully, catches its own logical faults, and verifies its outputs before reporting back.

2. Long-horizon agent reliability

  • Full 1M token context window at standard pricing, with state-of-the-art long-context consistency.
  • Far fewer tool errors, stronger recovery from tool failures, and better follow-through on multi-step workflows — designed for async work like CI/CD, automations, and managing multiple agents in parallel.
  • Stronger file-system-based memory, retaining useful notes across long, multi-session runs.

3. Sharper instruction following and honesty

  • Takes instructions literally and precisely — existing prompts may need re-tuning since earlier models were more lenient.
  • More honest about its own limits: reports missing data instead of fabricating plausible-but-wrong answers, and resists dissonant-data traps that tripped up Opus 4.6.

4. Substantially improved vision and multimodal reasoning

  • Accepts images up to 2,576 px on the long edge (~3.75 MP) — over 3x more than prior Claude models.
  • Unlocks dense-screenshot computer use, complex diagram extraction, and pixel-perfect reference tasks.
  • Stronger document reasoning for enterprise analysis (e.g., 21% fewer errors than Opus 4.6 on Databricks' OfficeQA Pro).

5. Top-tier professional knowledge work

  • State-of-the-art on the Finance Agent evaluation and GDPval-AA, with tighter, more professional finance analyses, models, and presentations.
  • Strong on legal work — e.g., 90.9% on BigLaw Bench at high effort, with better-calibrated reasoning on review tables and ambiguous edits.
  • Noted by design-focused partners as the best model for building dashboards and data-rich interfaces.

6. Modern effort and budget controls

  • Introduces a new xhigh effort level between high and max for finer control over reasoning vs. latency.
  • Task budgets (public beta) let developers guide token spend across long runs.
  • Recommended to start with high or xhigh effort for coding and agentic 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.

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