Model Comparison
Phi-4 Mini Instruct
vs. Qwen3 30B A3B 2507 (Reasoning)
Comparing 2 AI models · 12 benchmarks · Microsoft, Alibaba
Recommended Pick
AlQwen3 30B A3B 2507 (Reasoning)17 metric winsStrongest on: Throughput, Reasoning, Intelligence
Lowest Price
Phi-4 Mini Instruct
$0.00/1M input price
Best Reasoning
Qwen3 30B A3B 2507 (Reasoning)
56.5 reasoning score
Blends available reasoning benchmarks
Best for Coding
Qwen3 30B A3B 2507 (Reasoning)
12.1 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 30B A3B 2507 (Reasoning).
Speed gap
Qwen3 30B A3B 2507 (Reasoning) generates about 3.2x as many tokens per second as Phi-4 Mini Instruct.
Reasoning gap
Qwen3 30B A3B 2507 (Reasoning) leads Phi-4 Mini Instruct by 38.1 points on reasoning.
Coding gap
Qwen3 30B A3B 2507 (Reasoning) leads Phi-4 Mini Instruct by 8.3 points on coding.
Top-pick rationale
Qwen3 30B A3B 2507 (Reasoning) wins 17 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 30B A3B 2507 (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 30B A3B 2507 (Reasoning) |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.00/1M | $0.20/1M |
| Output Cost | $0.00/1M | $2.40/1M |
| Blended (3:1) | — | $0.75/1M |
| Specifications | ||
| Organization | Microsoft | Alibaba |
| Release Date | Feb 26, 2024 | Jul 30, 2025 |
| Performance & Speed | ||
| Throughput | 46.4 tok/s | 148.5 tok/s |
| TTFT | 326ms | 1067ms |
| Latency | 326ms | 14538ms |
| Composite Indices | ||
| Value Score | — | 100.0 |
| Reasoning Score | 18.5 | 56.5 |
| Intelligence | 6.0 | 14.4 |
| Coding | 3.8 | 12.1 |
| Math | 6.7 | 56.3 |
| Standard Benchmarks | ||
| GPQA | 33.1% | 70.7% |
| MMLU Pro | 46.5% | 80.5% |
| HLE | 4.2% | 9.8% |
| LiveCodeBench | 12.6% | 70.7% |
| MATH 500 | 69.6% | 97.6% |
| AIME 2025 | 6.7% | 56.3% |
| AIME (Original) | 3.0% | 90.7% |
| SciCode | 10.8% | 33.3% |
| LCR | 13.7% | 59.0% |
| IFBench | 21.1% | 50.7% |
| TAU-bench v2 | 8.2% | 28.1% |
| TerminalBench Hard | 0.0% | 5.3% |
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 30B A3B 2507 (Reasoning) has the strongest reasoning profile with a 56.5 reasoning score,combining the available reasoning-heavy benchmarks.
Qwen3 30B A3B 2507 (Reasoning) reaches a 12.1 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 30B A3B 2507 (Reasoning)
- Complex reasoning tasks
- Research & analysis
- Code generation
- Software development
