Model Comparison
o1-mini
vs. o3
Comparing 2 AI models · 12 benchmarks · OpenAI
Recommended Pick
Op o3 10 metric wins Strongest on: Throughput, Reasoning, Intelligence
Lowest Price
o1-mini
$0.00/1M input price
Best Reasoning
o3
71.3 reasoning score
Blends available reasoning benchmarks
Composite Indices
Higher is better; speed and price are normalized
Standard Benchmarks
Only benchmarks with data are shown
Differences That Matter
Price gap
o1-mini is ∞x cheaper on input tokens than o3.
Reasoning gap
o3 leads o1-mini by 24.5 points on reasoning.
Top-pick rationale
o3 wins 10 measurable categories, including Throughput, Reasoning, Intelligence, GPQA.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
o1-mini
OpenAI
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
o3
OpenAI
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Which answer was more useful?
Full Comparison
| Metric | Op o1-mini | Top Pick Op o3 |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.00/1M | $2.00/1M |
| Output Cost | $0.00/1M | $8.00/1M |
| Blended (3:1) | — | $3.50/1M |
| Specifications | ||
| Organization | OpenAI | OpenAI |
| Release Date | Sep 12, 2024 | Apr 16, 2025 |
| Performance & Speed | ||
| Throughput | — | 168.6 tok/s |
| TTFT | — | 6495ms |
| Latency | — | 6495ms |
| Composite Indices | ||
| Value Score | — | 100.0 |
| Reasoning Score | 46.8 | 71.3 |
| Intelligence | 14.0 | 30.4 |
| Math | — | 88.3 |
| Standard Benchmarks | ||
| GPQA | 60.3% | 82.7% |
| MMLU Pro | 74.2% | 85.3% |
| HLE | 4.9% | 20.0% |
| LiveCodeBench | 57.6% | 80.8% |
| MATH 500 | 94.4% | 99.2% |
| AIME 2025 | — | 88.3% |
| AIME (Original) | 60.3% | 90.3% |
| SciCode | 32.3% | 41.0% |
| LCR | — | 69.3% |
| IFBench | — | 71.4% |
| TAU-bench v2 | — | 80.7% |
| TerminalBench Hard | — | 37.1% |
Key Takeaways
o1-mini offers the best value at $0.00/1M, making it ideal for high-volume applications and cost-conscious projects.
o3 has the strongest reasoning profile with a 71.3 reasoning score, combining the available reasoning-heavy benchmarks.
All models support context windows of ∞+ tokens, suitable for processing lengthy documents and maintaining extended conversations.
When to Choose Each Model
o1-mini
- Cost-sensitive applications
- High-volume processing
o3
- Complex reasoning tasks
- Research & analysis
