o4-mini vs Claude 3.5 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. Intelligence & Reasoning

• Outperforms previous Claude models and competitor LLMs across major benchmarks.
• Excels in graduate-level reasoning (GPQA), knowledge tasks (MMLU), and coding (HumanEval).
• Handles nuance, humor, and complex instructions with human-like clarity.

2. Speed & Efficiency

• Runs 2x faster than Claude 3 Opus, making it ideal for real-time and high-volume workflows.
• Cost-effective pricing: $3/M input tokens and $15/M output tokens.
• Supports a 200K token context window, enabling rich, long-form reasoning.

3. Coding Capabilities

• Solves significantly more coding and bug-fix tasks (64% vs Opus's 38% in internal evaluations).
• Can autonomously write, edit, and execute code when tool use is enabled.
• Strong at translating and modernizing legacy codebases.

4. Vision Strength

• Best vision model in the Claude family, surpassing Opus on vision benchmarks.
• Excellent at interpreting charts, graphs, and imperfect images.
• Reliable text extraction from low-quality visuals for retail, logistics, finance, etc.

5. Agentic Workflows

• Highly capable for multi-step task orchestration.
• Performs well as the engine for agents requiring reasoning, planning, and tool-calling abilities.

6. Content Quality

• Produces natural, relatable writing with improved tone, style, and context awareness.
• Strong at long-form content creation and editing.

7. Safety & Reliability

• Rated ASL-2, meeting Anthropic's safety standards.
• Undergoes extensive red-teaming and external evaluation (UK AISI & US AISI).
• Not trained on user data without explicit permission.