Model Comparison
V3.1 (Non-reasoning)
vs. Qwen2.5 Instruct 72B
Comparing 2 AI models · 12 benchmarks · DeepSeek, Alibaba
Recommended Pick
De V3.1 (Non-reasoning) 14 metric wins Strongest on: Reasoning, Intelligence, Coding
Best Value
Qwen2.5 Instruct 72B
100.0 value score
28.4 reasoning / $0.37/1M
Lowest Price
Qwen2.5 Instruct 72B
$0.36/1M input price
Best Reasoning
V3.1 (Non-reasoning)
41.5 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
Qwen2.5 Instruct 72B has the strongest quality-to-price mix at 100.0 out of 100 value points.
Price gap
Qwen2.5 Instruct 72B is 1.5x cheaper on input tokens than V3.1 (Non-reasoning).
Reasoning gap
V3.1 (Non-reasoning) leads Qwen2.5 Instruct 72B by 13.1 points on reasoning.
Coding gap
V3.1 (Non-reasoning) leads Qwen2.5 Instruct 72B by 16.5 points on coding.
Top-pick rationale
V3.1 (Non-reasoning) wins 14 measurable categories, including Reasoning, Intelligence, Coding, Math.
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
—
Time
—
tok/s
—
Tokens
—
Cost
—
Qwen2.5 Instruct 72B
Alibaba
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Which answer was more useful?
Full Comparison
| Metric | Top Pick De V3.1 (Non-reasoning) | Al Qwen2.5 Instruct 72B |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.56/1M | $0.36/1M |
| Output Cost | $1.67/1M | $0.40/1M |
| Blended (3:1) | $0.83/1M | $0.37/1M |
| Specifications | ||
| Organization | DeepSeek | Alibaba |
| Release Date | Aug 21, 2025 | Sep 19, 2024 |
| Performance & Speed | ||
| Throughput | — | — |
| TTFT | — | — |
| Latency | — | — |
| Composite Indices | ||
| Value Score | 64.8 | 100.0 |
| Reasoning Score | 41.5 | 28.4 |
| Intelligence | 28.1 | 15.6 |
| Coding | 28.4 | 11.9 |
| Math | 49.7 | 14.0 |
| Standard Benchmarks | ||
| GPQA | 73.5% | 49.1% |
| MMLU Pro | 83.3% | 72.0% |
| HLE | 6.3% | 4.2% |
| LiveCodeBench | 57.7% | 27.6% |
| MATH 500 | — | 85.8% |
| AIME 2025 | 49.7% | 14.0% |
| AIME (Original) | — | 16.0% |
| SciCode | 36.7% | 26.7% |
| LCR | 45.0% | 20.3% |
| IFBench | 37.8% | 36.9% |
| TAU-bench v2 | 34.8% | 34.5% |
| TerminalBench Hard | 24.2% | 4.5% |
Key Takeaways
Qwen2.5 Instruct 72B offers the best value at $0.36/1M, making it ideal for high-volume applications and cost-conscious projects.
V3.1 (Non-reasoning) has the strongest reasoning profile with a 41.5 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)
- Complex reasoning tasks
- Research & analysis
- Code generation
- Software development
Qwen2.5 Instruct 72B
- Cost-sensitive applications
- High-volume processing
