Model Comparison
o4-mini (high)
vs. Qwen2.5 Instruct 32B
Comparing 2 AI models · 12 benchmarks · OpenAI, Alibaba
Recommended Pick
Opo4-mini (high)10 metric winsStrongest on: Throughput, Reasoning, Intelligence
Lowest Price
Qwen2.5 Instruct 32B
$0.00/1M input price
Best Reasoning
o4-mini (high)
70.8 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
Qwen2.5 Instruct 32B is ∞x cheaper on input tokens than o4-mini (high).
Reasoning gap
o4-mini (high) leads Qwen2.5 Instruct 32B by 40.9 points on reasoning.
Top-pick rationale
o4-mini (high) 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.
o4-mini (high)
OpenAI
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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Qwen2.5 Instruct 32B
Alibaba
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?
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Full Comparison
| Metric | Top Pick Op o4-mini (high) | Al Qwen2.5 Instruct 32B |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $1.10/1M | $0.00/1M |
| Output Cost | $4.40/1M | $0.00/1M |
| Blended (3:1) | $1.93/1M | — |
| Specifications | ||
| Organization | OpenAI | Alibaba |
| Release Date | Apr 16, 2025 | Sep 19, 2024 |
| Performance & Speed | ||
| Throughput | 187.3 tok/s | — |
| TTFT | 18672ms | — |
| Latency | 18672ms | — |
| Composite Indices | ||
| Value Score | 100.0 | — |
| Reasoning Score | 70.8 | 29.9 |
| Intelligence | 25.6 | 7.5 |
| Math | 90.7 | — |
| Standard Benchmarks | ||
| GPQA | 78.4% | 46.6% |
| MMLU Pro | 83.2% | 69.7% |
| HLE | 17.5% | 3.8% |
| LiveCodeBench | 85.9% | 24.8% |
| MATH 500 | 98.9% | 80.5% |
| AIME 2025 | 90.7% | — |
| AIME (Original) | 94.0% | 11.0% |
| SciCode | 46.5% | 22.9% |
| LCR | 55.0% | — |
| IFBench | 68.7% | — |
| TAU-bench v2 | 55.6% | — |
| TerminalBench Hard | 15.2% | — |
Key Takeaways
Qwen2.5 Instruct 32B offers the best value at $0.00/1M,making it ideal for high-volume applications and cost-conscious projects.
o4-mini (high) has the strongest reasoning profile with a 70.8 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
o4-mini (high)
- Complex reasoning tasks
- Research & analysis
Qwen2.5 Instruct 32B
- Cost-sensitive applications
- High-volume processing
