Model Comparison
o3-mini (high)
vs. Qwen3 32B (Non-reasoning)
Comparing 2 AI models · 12 benchmarks · OpenAI, Alibaba
Recommended Pick
Opo3-mini (high)13 metric winsStrongest on: Value, Throughput, Reasoning
Best Value
o3-mini (high)
100.0 value score
57.9 reasoning / $1.93/1M
Lowest Price
Qwen3 32B (Non-reasoning)
$0.70/1M input price
Best Reasoning
o3-mini (high)
57.9 reasoning score
Blends available reasoning benchmarks
Best for Coding
o3-mini (high)
16.3 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
o3-mini (high) has the strongest quality-to-price mix at 100.0 out of 100 value points.
Price gap
Qwen3 32B (Non-reasoning) is 1.6x cheaper on input tokens than o3-mini (high).
Speed gap
o3-mini (high) generates about 2.4x as many tokens per second as Qwen3 32B (Non-reasoning).
Reasoning gap
o3-mini (high) leads Qwen3 32B (Non-reasoning) by 26.1 points on reasoning.
Top-pick rationale
o3-mini (high) wins 13 measurable categories, including Value, Throughput, Reasoning, Intelligence.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
o3-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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Qwen3 32B (Non-reasoning)
Alibaba
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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Which answer was more useful?
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Full Comparison
| Metric | Top Pick Op o3-mini (high) | Al Qwen3 32B (Non-reasoning) |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $1.10/1M | $0.70/1M |
| Output Cost | $4.40/1M | $2.80/1M |
| Blended (3:1) | $1.93/1M | $1.22/1M |
| Specifications | ||
| Organization | OpenAI | Alibaba |
| Release Date | Jan 31, 2025 | Apr 28, 2025 |
| Performance & Speed | ||
| Throughput | 238.7 tok/s | 99.1 tok/s |
| TTFT | 18398ms | 1076ms |
| Latency | 18398ms | 1076ms |
| Composite Indices | ||
| Value Score | 100.0 | 86.4 |
| Reasoning Score | 57.9 | 31.9 |
| Intelligence | 15.6 | 8.6 |
| Coding | 16.3 | — |
| Math | — | 19.7 |
| Standard Benchmarks | ||
| GPQA | 77.3% | 53.5% |
| MMLU Pro | 80.2% | 72.7% |
| HLE | 12.3% | 4.3% |
| LiveCodeBench | 73.4% | 28.8% |
| MATH 500 | 98.5% | 86.9% |
| AIME 2025 | — | 19.7% |
| AIME (Original) | 86.0% | 30.3% |
| SciCode | 39.8% | 28.0% |
| LCR | 39.3% | 0.0% |
| IFBench | 67.1% | 31.5% |
| TAU-bench v2 | 31.3% | — |
| TerminalBench Hard | 6.1% | — |
Key Takeaways
Qwen3 32B (Non-reasoning) offers the best value at $0.70/1M,making it ideal for high-volume applications and cost-conscious projects.
o3-mini (high) has the strongest reasoning profile with a 57.9 reasoning score,combining the available reasoning-heavy benchmarks.
o3-mini (high) reaches a 16.3 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
o3-mini (high)
- Complex reasoning tasks
- Research & analysis
- Code generation
- Software development
Qwen3 32B (Non-reasoning)
- Cost-sensitive applications
- High-volume processing
