GPT-5 Mini vs Claude 4.5 Sonnet

Compare GPT-5 Mini and Claude 4.5 Sonnet. Find out which one is better for your use case.

Model Comparison

FeatureGPT-5 MiniClaude 4.5 Sonnet
ProviderOpenAIAnthropic
Model Typetexttext
Context Window400,000 tokens1,000,000 tokens
Input Cost$0.25 / 1M tokens$3.00 / 1M tokens
Output Cost$2.00 / 1M tokens$15.00 / 1M tokens

Strengths & Best Use Cases

GPT-5 Mini

1. High reasoning performance

  • Retains strong reasoning capabilities despite being a smaller, faster model.
  • Suitable for tasks requiring accurate logic and structured thinking.

2. Fast and cost-efficient

  • Optimized for speed, making it ideal for real-time or high-volume workloads.
  • Far cheaper than GPT-5 while maintaining solid capability.

3. Great for well-defined tasks

  • Excels when prompts are precise and objectives are clearly specified.
  • More predictable and stable for deterministic workflows.

4. Multimodal input

  • Accepts text + image as input.
  • Outputs text only.

5. Tool support

  • Works with Web Search, File Search, Code Interpreter, MCP.
  • (Does not support Image Generation as a tool and does not support Computer Use.)

Claude 4.5 Sonnet

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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