Model Comparison
Phi-4 Mini Instruct
vs. Qwen3.5 4B (Non-reasoning)
Comparing 2 AI models · 12 benchmarks · Microsoft, Alibaba
Recommended Pick
AlQwen3.5 4B (Non-reasoning)10 metric winsStrongest on: Reasoning, Intelligence, Coding
Lowest Price
Phi-4 Mini Instruct
$0.00/1M input price
Best Reasoning
Qwen3.5 4B (Non-reasoning)
31.6 reasoning score
Blends available reasoning benchmarks
Best for Coding
Qwen3.5 4B (Non-reasoning)
20.3 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 Qwen3.5 4B (Non-reasoning).
Speed gap
Phi-4 Mini Instruct generates about 1.6x as many tokens per second as Qwen3.5 4B (Non-reasoning).
Reasoning gap
Qwen3.5 4B (Non-reasoning) leads Phi-4 Mini Instruct by 13.1 points on reasoning.
Coding gap
Qwen3.5 4B (Non-reasoning) leads Phi-4 Mini Instruct by 16.5 points on coding.
Top-pick rationale
Qwen3.5 4B (Non-reasoning) wins 10 measurable categories, including Reasoning, Intelligence, Coding, 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
—
Time
—
tok/s
—
Tokens
—
Cost
—
Qwen3.5 4B (Non-reasoning)
Alibaba
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Which answer was more useful?
Chat with leading AI models
Use Claude, ChatGPT, Gemini alongside with EU-Hosted Models like Deepseek, Qwen & Kimi.
EU-hosted inference
Servers in Germany & Finland. Designed to meet strict GDPR and ISO 27001 compliance requirements.
Full Comparison
| Metric | Mi Phi-4 Mini Instruct | Top Pick Al Qwen3.5 4B (Non-reasoning) |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.00/1M | $0.03/1M |
| Output Cost | $0.00/1M | $0.15/1M |
| Blended (3:1) | — | $0.06/1M |
| Specifications | ||
| Organization | Microsoft | Alibaba |
| Release Date | Feb 26, 2024 | Mar 2, 2026 |
| Performance & Speed | ||
| Throughput | 46.2 tok/s | 28.3 tok/s |
| TTFT | 338ms | 430ms |
| Latency | 338ms | 430ms |
| Composite Indices | ||
| Value Score | — | 100.0 |
| Reasoning Score | 18.5 | 31.6 |
| Intelligence | 6.0 | 16.0 |
| Coding | 3.8 | 20.3 |
| Math | 6.7 | — |
| Standard Benchmarks | ||
| GPQA | 33.1% | 71.2% |
| MMLU Pro | 46.5% | — |
| HLE | 4.2% | 7.5% |
| LiveCodeBench | 12.6% | — |
| MATH 500 | 69.6% | — |
| AIME 2025 | 6.7% | — |
| AIME (Original) | 3.0% | — |
| SciCode | 10.8% | 18.3% |
| LCR | 13.7% | 28.3% |
| IFBench | 21.1% | 33.3% |
| TAU-bench v2 | 8.2% | 87.7% |
| TerminalBench Hard | 0.0% | 11.4% |
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.
Qwen3.5 4B (Non-reasoning) has the strongest reasoning profile with a 31.6 reasoning score,combining the available reasoning-heavy benchmarks.
Qwen3.5 4B (Non-reasoning) reaches a 20.3 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
Qwen3.5 4B (Non-reasoning)
- Complex reasoning tasks
- Research & analysis
- Code generation
- Software development
