Model Comparison
o3-mini
vs. QwQ 32B
Comparing 2 AI models · 12 benchmarks · OpenAI, Alibaba
Recommended Pick
Opo3-mini10 metric winsStrongest on: Throughput, Latency, Reasoning
Best Value
QwQ 32B
100.0 value score
44.7 reasoning / $0.74/1M
Lowest Price
QwQ 32B
$0.66/1M input price
Best Reasoning
o3-mini
55.4 reasoning score
Blends available reasoning benchmarks
Composite Indices
Higher is better; speed and price are normalized
Standard Benchmarks
Only benchmarks with data are shown
Differences That Matter
Best value
QwQ 32B has the strongest quality-to-price mix at 100.0 out of 100 value points.
Price gap
QwQ 32B is 1.7x cheaper on input tokens than o3-mini.
Speed gap
o3-mini generates about 6.8x as many tokens per second as QwQ 32B.
Reasoning gap
o3-mini leads QwQ 32B by 10.7 points on reasoning.
Top-pick rationale
o3-mini wins 10 measurable categories, including Throughput, Latency, Reasoning, Intelligence.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
o3-mini
OpenAI
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
QwQ 32B
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 | Al QwQ 32B |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $1.10/1M | $0.66/1M |
| Output Cost | $4.40/1M | $1.00/1M |
| Blended (3:1) | $1.93/1M | $0.74/1M |
| Specifications | ||
| Organization | OpenAI | Alibaba |
| Release Date | Jan 31, 2025 | Mar 5, 2025 |
| Performance & Speed | ||
| Throughput | 224.2 tok/s | 33.1 tok/s |
| TTFT | 5719ms | 568ms |
| Latency | 5719ms | 75825ms |
| Composite Indices | ||
| Value Score | 48.0 | 100.0 |
| Reasoning Score | 55.4 | 44.7 |
| Intelligence | 19.0 | 13.4 |
| Math | — | 29.0 |
| Standard Benchmarks | ||
| GPQA | 74.8% | 59.3% |
| MMLU Pro | 79.1% | 76.4% |
| HLE | 8.7% | 8.2% |
| LiveCodeBench | 71.7% | 63.1% |
| MATH 500 | 97.3% | 95.7% |
| AIME 2025 | — | 29.0% |
| AIME (Original) | 77.0% | 78.0% |
| SciCode | 39.9% | 35.8% |
| LCR | — | 25.0% |
| IFBench | — | 38.8% |
| TAU-bench v2 | 28.7% | — |
| TerminalBench Hard | 6.8% | — |
Key Takeaways
QwQ 32B offers the best value at $0.66/1M,making it ideal for high-volume applications and cost-conscious projects.
o3-mini has the strongest reasoning profile with a 55.4 reasoning score,combining the available reasoning-heavy benchmarks.
All models support context windows of ∞+ tokens,suitable for processing lengthy documents and maintaining extended conversations.
When to Choose Each Model
o3-mini
- Complex reasoning tasks
- Research & analysis
QwQ 32B
- Cost-sensitive applications
- High-volume processing
