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LLM ComparisonGPT-5Claude 4.5 Sonnet

GPT-5 vs Claude 4.5 Sonnet

Compare GPT-5 and Claude 4.5 Sonnet. Build AI products powered by either model on Appaca.

Model Comparison

FeatureGPT-5Claude 4.5 Sonnet
ProviderOpenAIAnthropic
Model Typetexttext
Context Window400,000 tokens1,000,000 tokens
Input Cost
$1.25/ 1M tokens
$3.00/ 1M tokens
Output Cost
$10.00/ 1M tokens
$15.00/ 1M tokens

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Strengths & Best Use Cases

GPT-5

OpenAI

1. High reasoning capability

  • Designed for intelligent reasoning across complex domains.
  • Supports reasoning tokens and adjustable reasoning effort.

2. Strong coding and agentic performance

  • Optimized for multi-step coding tasks, tool-use chains, and agent workflows.
  • Handles complex logic, planning, and structured problem solving reliably.

3. Multimodal input

  • Accepts text + image as input.
  • Produces text outputs with strong instruction following.

4. Extensive tool support

  • Works with Web Search, File Search, Image Generation (as a tool), Code Interpreter, MCP, and more.
  • Integrated across Chat Completions, Responses API, Realtime, Assistants, Batch, Embeddings, etc.

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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