Model Comparison
Phi-4 Mini Instruct
vs. Qwen3 32B (Reasoning)
Comparing 2 AI models · 12 benchmarks · Microsoft, Alibaba
Recommended Pick
AlQwen3 32B (Reasoning)16 metric winsStrongest on: Throughput, Reasoning, Intelligence
Lowest Price
Phi-4 Mini Instruct
$0.00/1M input price
Best Reasoning
Qwen3 32B (Reasoning)
58.5 reasoning score
Blends available reasoning benchmarks
Best for Coding
Qwen3 32B (Reasoning)
15.3 coding index
Composite Indices
Higher is better; speed and price are normalized
Standard Benchmarks
Only benchmarks with data are shown
Differences That Matter
Price gap
Phi-4 Mini Instruct is ∞x cheaper on input tokens than Qwen3 32B (Reasoning).
Speed gap
Qwen3 32B (Reasoning) generates about 2.1x as many tokens per second as Phi-4 Mini Instruct.
Reasoning gap
Qwen3 32B (Reasoning) leads Phi-4 Mini Instruct by 40.0 points on reasoning.
Coding gap
Qwen3 32B (Reasoning) leads Phi-4 Mini Instruct by 11.5 points on coding.
Top-pick rationale
Qwen3 32B (Reasoning) wins 16 measurable categories, including Throughput, Reasoning, Intelligence, Coding.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
Phi-4 Mini Instruct
Microsoft
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 (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 | Mi Phi-4 Mini Instruct | Top Pick Al Qwen3 32B (Reasoning) |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.00/1M | $0.70/1M |
| Output Cost | $0.00/1M | $8.40/1M |
| Blended (3:1) | — | $2.63/1M |
| Specifications | ||
| Organization | Microsoft | Alibaba |
| Release Date | Feb 26, 2024 | Apr 28, 2025 |
| Performance & Speed | ||
| Throughput | 46.3 tok/s | 96.9 tok/s |
| TTFT | 338ms | 1066ms |
| Latency | 338ms | 21714ms |
| Composite Indices | ||
| Value Score | — | 100.0 |
| Reasoning Score | 18.5 | 58.5 |
| Intelligence | 6.0 | 11.5 |
| Coding | 3.8 | 15.3 |
| Math | 6.7 | 73.0 |
| Standard Benchmarks | ||
| GPQA | 33.1% | 66.8% |
| MMLU Pro | 46.5% | 79.8% |
| HLE | 4.2% | 8.3% |
| LiveCodeBench | 12.6% | 54.6% |
| MATH 500 | 69.6% | 96.1% |
| AIME 2025 | 6.7% | 73.0% |
| AIME (Original) | 3.0% | 80.7% |
| SciCode | 10.8% | 35.4% |
| LCR | 13.7% | 0.0% |
| IFBench | 21.1% | 36.3% |
| TAU-bench v2 | 8.2% | 29.8% |
| TerminalBench Hard | 0.0% | 3.0% |
Key Takeaways
Phi-4 Mini Instruct offers the best value at $0.00/1M,making it ideal for high-volume applications and cost-conscious projects.
Qwen3 32B (Reasoning) has the strongest reasoning profile with a 58.5 reasoning score,combining the available reasoning-heavy benchmarks.
Qwen3 32B (Reasoning) reaches a 15.3 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
Phi-4 Mini Instruct
- Cost-sensitive applications
- High-volume processing
Qwen3 32B (Reasoning)
- Complex reasoning tasks
- Research & analysis
- Code generation
- Software development
