GPT-4o mini vs OpenAI o3-mini
Detailed performance comparison across SWE-bench Verified, LiveCodeBench, AIME, GPQA Diamond, pricing per million tokens, and hardware requirements.
High-speed, ultra-affordable multimodal small model designed to replace GPT-3.5 Turbo at 60% lower cost.
Next-generation cost-efficient reasoning model optimized for STEM, competitive math, and coding.
Key Strengths & Architectural Trade-offs
Direct synthesis of practical production advantages and limitations.
GPT-4o mini
- Incredible cost-to-performance ratio ($0.15 / MTok input)
- Multimodal vision capabilities at budget pricing
- High throughput rate limits on OpenAI platform
- Lower accuracy on deep mathematical proofs and Olympic competitions
- Context window limited to 128k tokens
OpenAI o3-mini
- Exceptional cost-to-reasoning ratio ($1.10 / $4.40 per MTok)
- 87.3% on AIME 2024 (high effort)
- Full support for tool calling, structured output, and developer messages
- Text-only model; vision inputs are not supported
- Reasoning token usage consumes output token budget
Recommended Use Cases by Workload
- •High-volume content moderation & classification
- •Customer support chatbots
- •Lightweight data parsing & batch JSON conversion
- •Competitive math & algorithmic coding pipelines
- •Automated code review & unit test synthesis
- •High-complexity agent reasoning steps at affordable cost
Data Accuracy & Verification Notice
AI model specifications, pricing records, and benchmark metrics published on this platform are compiled directly from authoritative sources (official provider documentation, research papers, and verified evaluation harnesses). Benchmark results reflect specific test harnesses and prompting methodologies; scores are not directly comparable across differing evaluation setups.
Select 2 to 5 Models to Compare
Compare benchmark scores, architecture, context limits, pricing, and hardware requirements side-by-side.
Choose from Model Catalog (18 models)
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