Model Comparison
o3-mini (high)
vs. Qwen3 1.7B (Reasoning)
Comparing 2 AI models · 12 benchmarks · OpenAI, Alibaba
Recommended Pick
Opo3-mini (high)14 metric winsStrongest on: Throughput, Reasoning, Intelligence
Lowest Price
Qwen3 1.7B (Reasoning)
$0.00/1M input price
Best Reasoning
o3-mini (high)
57.9 reasoning score
Blends available reasoning benchmarks
Best for Coding
o3-mini (high)
16.3 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
Qwen3 1.7B (Reasoning) is ∞x cheaper on input tokens than o3-mini (high).
Reasoning gap
o3-mini (high) leads Qwen3 1.7B (Reasoning) by 20.7 points on reasoning.
Top-pick rationale
o3-mini (high) wins 14 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.
o3-mini (high)
OpenAI
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Qwen3 1.7B (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 | Top Pick Op o3-mini (high) | Al Qwen3 1.7B (Reasoning) |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $1.10/1M | $0.00/1M |
| Output Cost | $4.40/1M | $0.00/1M |
| Blended (3:1) | $1.93/1M | — |
| Specifications | ||
| Organization | OpenAI | Alibaba |
| Release Date | Jan 31, 2025 | Apr 28, 2025 |
| Performance & Speed | ||
| Throughput | 241.1 tok/s | — |
| TTFT | 16665ms | — |
| Latency | 16665ms | — |
| Composite Indices | ||
| Value Score | 100.0 | — |
| Reasoning Score | 57.9 | 37.3 |
| Intelligence | 15.6 | 2.6 |
| Coding | 16.3 | — |
| Math | — | 38.7 |
| Standard Benchmarks | ||
| GPQA | 77.3% | 35.6% |
| MMLU Pro | 80.2% | 57.0% |
| HLE | 12.3% | 4.8% |
| LiveCodeBench | 73.4% | 30.8% |
| MATH 500 | 98.5% | 89.4% |
| AIME 2025 | — | 38.7% |
| AIME (Original) | 86.0% | 51.0% |
| SciCode | 39.8% | 4.3% |
| LCR | 39.3% | 0.0% |
| IFBench | 67.1% | 26.9% |
| TAU-bench v2 | 31.3% | 26.0% |
| TerminalBench Hard | 6.1% | 0.0% |
Key Takeaways
Qwen3 1.7B (Reasoning) offers the best value at $0.00/1M,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.
o3-mini (high) reaches a 16.3 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
- Code generation
- Software development
Qwen3 1.7B (Reasoning)
- Cost-sensitive applications
- High-volume processing
