Model Comparison
o3-mini (high)
vs. Qwen3.5 4B (Non-reasoning)
Comparing 2 AI models · 11 benchmarks · OpenAI, Alibaba
Recommended Pick
AlQwen3.5 4B (Non-reasoning)10 metric winsStrongest on: Value, Input price, Output price
Best Value
Qwen3.5 4B (Non-reasoning)
100.0 value score
31.6 reasoning / $0.06/1M
Lowest Price
Qwen3.5 4B (Non-reasoning)
$0.03/1M input price
Best Reasoning
o3-mini (high)
57.9 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
Best value
Qwen3.5 4B (Non-reasoning) has the strongest quality-to-price mix at 100.0 out of 100 value points.
Price gap
Qwen3.5 4B (Non-reasoning) is 36.7x cheaper on input tokens than o3-mini (high).
Speed gap
o3-mini (high) generates about 8.7x as many tokens per second as Qwen3.5 4B (Non-reasoning).
Reasoning gap
o3-mini (high) leads Qwen3.5 4B (Non-reasoning) by 26.4 points on reasoning.
Coding gap
Qwen3.5 4B (Non-reasoning) leads o3-mini (high) by 4.0 points on coding.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
o3-mini (high)
OpenAI
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 | Op o3-mini (high) | Top Pick Al Qwen3.5 4B (Non-reasoning) |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $1.10/1M | $0.03/1M |
| Output Cost | $4.40/1M | $0.15/1M |
| Blended (3:1) | $1.93/1M | $0.06/1M |
| Specifications | ||
| Organization | OpenAI | Alibaba |
| Release Date | Jan 31, 2025 | Mar 2, 2026 |
| Performance & Speed | ||
| Throughput | 236.2 tok/s | 27.0 tok/s |
| TTFT | 16663ms | 430ms |
| Latency | 16663ms | 430ms |
| Composite Indices | ||
| Value Score | 5.7 | 100.0 |
| Reasoning Score | 57.9 | 31.6 |
| Intelligence | 15.6 | 16.0 |
| Coding | 16.3 | 20.3 |
| Standard Benchmarks | ||
| GPQA | 77.3% | 71.2% |
| MMLU Pro | 80.2% | — |
| HLE | 12.3% | 7.5% |
| LiveCodeBench | 73.4% | — |
| MATH 500 | 98.5% | — |
| AIME (Original) | 86.0% | — |
| SciCode | 39.8% | 18.3% |
| LCR | 39.3% | 28.3% |
| IFBench | 67.1% | 33.3% |
| TAU-bench v2 | 31.3% | 87.7% |
| TerminalBench Hard | 6.1% | 11.4% |
Key Takeaways
Qwen3.5 4B (Non-reasoning) offers the best value at $0.03/1M,making it ideal for high-volume applications and cost-conscious projects.
o3-mini (high) has the strongest reasoning profile with a 57.9 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
o3-mini (high)
- Complex reasoning tasks
- Research & analysis
Qwen3.5 4B (Non-reasoning)
- Cost-sensitive applications
- High-volume processing
- Code generation
- Software development
