Model Comparison
o1-mini
vs. M3
Comparing 2 AI models · 11 benchmarks · OpenAI, MiniMax
Recommended Pick
Mi M3 5 metric wins Strongest on: Reasoning, Intelligence, GPQA
Lowest Price
o1-mini
$0.00/1M input price
Best Reasoning
M3
61.6 reasoning score
Blends available reasoning benchmarks
Best for Coding
M3
43.4 coding index
Composite Indices
Higher is better; speed and price are normalized
Standard Benchmarks
Only benchmarks with data are shown
Differences That Matter
Reasoning gap
M3 leads o1-mini by 13.5 points on reasoning.
Top-pick rationale
M3 wins 5 measurable categories, including Reasoning, Intelligence, GPQA, HLE.
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
—
M3
MiniMax
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Which answer was more useful?
Full Comparison
| Metric | Op o1-mini | Top Pick Mi M3 |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.00/1M | $0.00/1M |
| Output Cost | $0.00/1M | $0.00/1M |
| Specifications | ||
| Organization | OpenAI | MiniMax |
| Release Date | Sep 12, 2024 | Jun 1, 2026 |
| Performance & Speed | ||
| Throughput | — | — |
| TTFT | — | — |
| Latency | — | — |
| Composite Indices | ||
| Reasoning Score | 48.1 | 61.6 |
| Intelligence | 20.4 | 54.7 |
| Coding | — | 43.4 |
| Standard Benchmarks | ||
| GPQA | 60.3% | 92.9% |
| MMLU Pro | 74.2% | — |
| HLE | 4.9% | 37.1% |
| LiveCodeBench | 57.6% | — |
| MATH 500 | 94.4% | — |
| AIME (Original) | 60.3% | — |
| SciCode | 32.3% | 45.4% |
| LCR | — | 74.0% |
| IFBench | — | 82.9% |
| TAU-bench v2 | — | 88.9% |
| TerminalBench Hard | — | 42.4% |
Key Takeaways
o1-mini offers the best value at $0.00/1M, making it ideal for high-volume applications and cost-conscious projects.
M3 has the strongest reasoning profile with a 61.6 reasoning score, combining the available reasoning-heavy benchmarks.
M3 reaches a 43.4 coding index, making it the top choice for software development and code generation tasks.
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
M3
- Complex reasoning tasks
- Research & analysis
- Code generation
- Software development
