Model Comparison
Phi-4 Mini Instruct
vs. Qwen2.5 Turbo
Comparing 2 AI models · 12 benchmarks · Microsoft, Alibaba
Recommended Pick
AlQwen2.5 Turbo9 metric winsStrongest on: Throughput, Reasoning, Intelligence
Lowest Price
Phi-4 Mini Instruct
$0.00/1M input price
Best Reasoning
Qwen2.5 Turbo
28.8 reasoning score
Blends available reasoning benchmarks
Best for Coding
Phi-4 Mini Instruct
3.8 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 Qwen2.5 Turbo.
Speed gap
Qwen2.5 Turbo generates about 2.5x as many tokens per second as Phi-4 Mini Instruct.
Reasoning gap
Qwen2.5 Turbo leads Phi-4 Mini Instruct by 10.3 points on reasoning.
Top-pick rationale
Qwen2.5 Turbo wins 9 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.
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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Qwen2.5 Turbo
Alibaba
TTFT
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Time
—
tok/s
—
Tokens
—
Cost
—
Which answer was more useful?
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Full Comparison
| Metric | Mi Phi-4 Mini Instruct | Top Pick Al Qwen2.5 Turbo |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.00/1M | $0.05/1M |
| Output Cost | $0.00/1M | $0.20/1M |
| Blended (3:1) | — | $0.09/1M |
| Specifications | ||
| Organization | Microsoft | Alibaba |
| Release Date | Feb 26, 2024 | Nov 18, 2024 |
| Performance & Speed | ||
| Throughput | 46.3 tok/s | 114.3 tok/s |
| TTFT | 338ms | 1062ms |
| Latency | 338ms | 1062ms |
| Composite Indices | ||
| Value Score | — | 100.0 |
| Reasoning Score | 18.5 | 28.8 |
| Intelligence | 6.0 | 6.3 |
| Coding | 3.8 | — |
| Math | 6.7 | — |
| Standard Benchmarks | ||
| GPQA | 33.1% | 41.0% |
| MMLU Pro | 46.5% | 63.3% |
| HLE | 4.2% | 4.2% |
| LiveCodeBench | 12.6% | 16.3% |
| MATH 500 | 69.6% | 80.5% |
| AIME 2025 | 6.7% | — |
| AIME (Original) | 3.0% | 12.0% |
| SciCode | 10.8% | 15.3% |
| LCR | 13.7% | — |
| IFBench | 21.1% | — |
| TAU-bench v2 | 8.2% | — |
| TerminalBench Hard | 0.0% | — |
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.
Qwen2.5 Turbo has the strongest reasoning profile with a 28.8 reasoning score,combining the available reasoning-heavy benchmarks.
Phi-4 Mini Instruct reaches a 3.8 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
- Code generation
- Software development
Qwen2.5 Turbo
- Complex reasoning tasks
- Research & analysis
