Model Comparison
R1 (Jan '25)
vs. V3.1 (Reasoning)
Comparing 2 AI models · 12 benchmarks · DeepSeek
Recommended Pick
De V3.1 (Reasoning) 18 metric wins Strongest on: Value, Input price, Output price
Best Value
V3.1 (Reasoning)
100.0 value score
59.6 reasoning / $0.86/1M
Lowest Price
V3.1 (Reasoning)
$0.59/1M input price
Best Reasoning
V3.1 (Reasoning)
59.6 reasoning score
Blends available reasoning benchmarks
Best for Coding
V3.1 (Reasoning)
29.7 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 (Reasoning) has the strongest quality-to-price mix at 100.0 out of 100 value points.
Price gap
V3.1 (Reasoning) is 2.8x cheaper on input tokens than R1 (Jan '25).
Reasoning gap
V3.1 (Reasoning) leads R1 (Jan '25) by 2.5 points on reasoning.
Coding gap
V3.1 (Reasoning) leads R1 (Jan '25) by 13.8 points on coding.
Top-pick rationale
V3.1 (Reasoning) wins 18 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.
R1 (Jan '25)
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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V3.1 (Reasoning)
DeepSeek
TTFT
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Time
—
tok/s
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Tokens
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Cost
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Which answer was more useful?
Full Comparison
| Metric | De R1 (Jan '25) | Top Pick De V3.1 (Reasoning) |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $1.68/1M | $0.59/1M |
| Output Cost | $4.70/1M | $1.69/1M |
| Blended (3:1) | $2.43/1M | $0.86/1M |
| Specifications | ||
| Organization | DeepSeek | DeepSeek |
| Release Date | Jan 20, 2025 | Aug 21, 2025 |
| Performance & Speed | ||
| Throughput | — | — |
| TTFT | — | — |
| Latency | — | — |
| Composite Indices | ||
| Value Score | 34.1 | 100.0 |
| Reasoning Score | 57.1 | 59.6 |
| Intelligence | 18.8 | 27.7 |
| Coding | 15.9 | 29.7 |
| Math | 68.0 | 89.7 |
| Standard Benchmarks | ||
| GPQA | 70.8% | 77.9% |
| MMLU Pro | 84.4% | 85.1% |
| HLE | 9.3% | 13.0% |
| LiveCodeBench | 61.7% | 78.4% |
| MATH 500 | 96.6% | — |
| AIME 2025 | 68.0% | 89.7% |
| AIME (Original) | 68.3% | — |
| SciCode | 35.7% | 39.1% |
| LCR | 52.3% | 53.3% |
| IFBench | 39.0% | 41.5% |
| TAU-bench v2 | 11.4% | 37.4% |
| TerminalBench Hard | 6.1% | 25.0% |
Key Takeaways
V3.1 (Reasoning) offers the best value at $0.59/1M, making it ideal for high-volume applications and cost-conscious projects.
V3.1 (Reasoning) has the strongest reasoning profile with a 59.6 reasoning score, combining the available reasoning-heavy benchmarks.
V3.1 (Reasoning) reaches a 29.7 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
R1 (Jan '25)
- General-purpose AI
- Versatile applications
V3.1 (Reasoning)
- Cost-sensitive applications
- High-volume processing
- Complex reasoning tasks
- Research & analysis
- Code generation
- Software development
