Model Comparison
V3.1 (Non-reasoning)
vs. o3-mini (high)
Comparing 2 AI models · 12 benchmarks · DeepSeek, OpenAI
Recommended Pick
De V3.1 (Non-reasoning) 12 metric wins Strongest on: Value, Input price, Output price
Best Value
V3.1 (Non-reasoning)
100.0 value score
41.5 reasoning / $0.83/1M
Lowest Price
V3.1 (Non-reasoning)
$0.56/1M input price
Best Reasoning
o3-mini (high)
59.9 reasoning score
Blends available reasoning benchmarks
Best for Coding
V3.1 (Non-reasoning)
28.4 coding index
Composite Indices
Higher is better; speed and price are normalized
Standard Benchmarks
Only benchmarks with data are shown
Differences That Matter
Best value
V3.1 (Non-reasoning) has the strongest quality-to-price mix at 100.0 out of 100 value points.
Price gap
V3.1 (Non-reasoning) is 2.0x cheaper on input tokens than o3-mini (high).
Reasoning gap
o3-mini (high) leads V3.1 (Non-reasoning) by 18.4 points on reasoning.
Coding gap
V3.1 (Non-reasoning) leads o3-mini (high) by 11.1 points on coding.
Top-pick rationale
V3.1 (Non-reasoning) wins 12 measurable categories, including Value, Input price, Output price, Blended price.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
V3.1 (Non-reasoning)
DeepSeek
TTFT
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Time
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tok/s
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Tokens
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Cost
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o3-mini (high)
OpenAI
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Which answer was more useful?
Full Comparison
| Metric | Top Pick De V3.1 (Non-reasoning) | Op o3-mini (high) |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.56/1M | $1.10/1M |
| Output Cost | $1.67/1M | $4.40/1M |
| Blended (3:1) | $0.83/1M | $1.93/1M |
| Specifications | ||
| Organization | DeepSeek | OpenAI |
| Release Date | Aug 21, 2025 | Jan 31, 2025 |
| Performance & Speed | ||
| Throughput | — | 223.7 tok/s |
| TTFT | — | 22505ms |
| Latency | — | 22505ms |
| Composite Indices | ||
| Value Score | 100.0 | 62.5 |
| Reasoning Score | 41.5 | 59.9 |
| Intelligence | 28.1 | 25.2 |
| Coding | 28.4 | 17.3 |
| Math | 49.7 | — |
| Standard Benchmarks | ||
| GPQA | 73.5% | 77.3% |
| MMLU Pro | 83.3% | 80.2% |
| HLE | 6.3% | 12.3% |
| LiveCodeBench | 57.7% | 73.4% |
| MATH 500 | — | 98.5% |
| AIME 2025 | 49.7% | — |
| AIME (Original) | — | 86.0% |
| SciCode | 36.7% | 39.8% |
| LCR | 45.0% | 39.3% |
| IFBench | 37.8% | 67.1% |
| TAU-bench v2 | 34.8% | 31.3% |
| TerminalBench Hard | 24.2% | 6.1% |
Key Takeaways
V3.1 (Non-reasoning) offers the best value at $0.56/1M, making it ideal for high-volume applications and cost-conscious projects.
o3-mini (high) has the strongest reasoning profile with a 59.9 reasoning score, combining the available reasoning-heavy benchmarks.
V3.1 (Non-reasoning) reaches a 28.4 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
V3.1 (Non-reasoning)
- Cost-sensitive applications
- High-volume processing
- Code generation
- Software development
o3-mini (high)
- Complex reasoning tasks
- Research & analysis
