o4-mini vs Claude 4.5 Sonnet

1. Fast and efficient reasoning

• Provides strong reasoning capabilities with significantly lower latency and cost compared to larger o-series models.
• Ideal for lightweight reasoning tasks, logic steps, and quick multi-step thinking.

2. Optimized for coding tasks

• Performs exceptionally well in code generation, debugging, and explanation.
• Useful for IDE integrations, coding assistants, and developer tools with tight latency budgets.

3. Strong visual reasoning

• Accepts image inputs for tasks such as diagram interpretation, charts, UI analysis, and visual logic.
• Great for hybrid text-image reasoning flows.

4. Large 200K-token context window

• Capable of processing long documents, multi-file codebases, or extended analysis.
• Reduces need for chunking or external retrieval pipelines.

5. High 100K-token output limit

• Supports lengthy reasoning sequences, full codebase explanations, or multi-section documents.

6. Broad API compatibility

• Available in Chat Completions, Responses, Realtime, Assistants, Batch, Embeddings, and Image workflows.
• Supports streaming, function calling, structured outputs, and fine-tuning.

7. Cost-efficient for production

• Lower input/output pricing makes it suitable for large-scale deployments, SaaS products, and recurring tasks.

8. Succeeded by GPT-5 mini

• GPT-5 mini offers improved speed, reasoning power, and pricing, but o4-mini remains a strong option for cost-sensitive workloads.

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.