Model Comparison
Phi-3 Mini Instruct 3.8B
vs. Qwen3.6 27B (Non-reasoning)
Comparing 2 AI models · 12 benchmarks · Microsoft, Alibaba
Recommended Pick
AlQwen3.6 27B (Non-reasoning)10 metric winsStrongest on: Throughput, Reasoning, Intelligence
Lowest Price
Phi-3 Mini Instruct 3.8B
$0.00/1M input price
Best Reasoning
Qwen3.6 27B (Non-reasoning)
42.3 reasoning score
Blends available reasoning benchmarks
Best for Coding
Qwen3.6 27B (Non-reasoning)
46.6 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-3 Mini Instruct 3.8B is ∞x cheaper on input tokens than Qwen3.6 27B (Non-reasoning).
Reasoning gap
Qwen3.6 27B (Non-reasoning) leads Phi-3 Mini Instruct 3.8B by 29.3 points on reasoning.
Top-pick rationale
Qwen3.6 27B (Non-reasoning) 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.
Phi-3 Mini Instruct 3.8B
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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Qwen3.6 27B (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 | Mi Phi-3 Mini Instruct 3.8B | Top Pick Al Qwen3.6 27B (Non-reasoning) |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.00/1M | $0.60/1M |
| Output Cost | $0.00/1M | $3.60/1M |
| Blended (3:1) | — | $1.35/1M |
| Specifications | ||
| Organization | Microsoft | Alibaba |
| Release Date | Apr 23, 2024 | Apr 22, 2026 |
| Performance & Speed | ||
| Throughput | — | 63.3 tok/s |
| TTFT | — | 1354ms |
| Latency | — | 1354ms |
| Composite Indices | ||
| Value Score | — | 100.0 |
| Reasoning Score | 13.0 | 42.3 |
| Intelligence | 4.6 | 30.5 |
| Coding | — | 46.6 |
| Math | 0.3 | — |
| Standard Benchmarks | ||
| GPQA | 31.9% | 82.9% |
| MMLU Pro | 43.5% | — |
| HLE | 4.4% | 13.6% |
| LiveCodeBench | 11.6% | — |
| MATH 500 | 45.7% | — |
| AIME 2025 | 0.3% | — |
| AIME (Original) | 4.0% | — |
| SciCode | 9.0% | 37.3% |
| LCR | 2.0% | 55.0% |
| IFBench | 23.9% | 45.7% |
| TAU-bench v2 | 0.0% | 93.6% |
| TerminalBench Hard | 0.0% | 21.2% |
Key Takeaways
Phi-3 Mini Instruct 3.8B offers the best value at $0.00/1M,making it ideal for high-volume applications and cost-conscious projects.
Qwen3.6 27B (Non-reasoning) has the strongest reasoning profile with a 42.3 reasoning score,combining the available reasoning-heavy benchmarks.
Qwen3.6 27B (Non-reasoning) reaches a 46.6 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-3 Mini Instruct 3.8B
- Cost-sensitive applications
- High-volume processing
Qwen3.6 27B (Non-reasoning)
- Complex reasoning tasks
- Research & analysis
- Code generation
- Software development
