Model Comparison
QwQ 32B
vs. Sonar
Comparing 2 AI models · 10 benchmarks · Alibaba, Perplexity
Recommended Pick
Al QwQ 32B 10 metric wins Strongest on: Throughput, Reasoning, Intelligence
Lowest Price
Sonar
$0.00/1M input price
Best Reasoning
QwQ 32B
45.6 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
Price gap
Sonar is ∞x cheaper on input tokens than QwQ 32B.
Reasoning gap
QwQ 32B leads Sonar by 5.5 points on reasoning.
Top-pick rationale
QwQ 32B 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.
QwQ 32B
Alibaba
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Sonar
Perplexity
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Which answer was more useful?
Full Comparison
| Metric | Top Pick Al QwQ 32B | Pe Sonar |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.66/1M | $0.00/1M |
| Output Cost | $1.00/1M | $0.00/1M |
| Blended (3:1) | $0.74/1M | — |
| Specifications | ||
| Organization | Alibaba | Perplexity |
| Release Date | Mar 5, 2025 | Jan 21, 2025 |
| Performance & Speed | ||
| Throughput | 30.9 tok/s | — |
| TTFT | 431ms | — |
| Latency | 80963ms | — |
| Composite Indices | ||
| Value Score | 100.0 | — |
| Reasoning Score | 45.6 | 40.0 |
| Intelligence | 19.7 | 15.5 |
| Math | 29.0 | — |
| Standard Benchmarks | ||
| GPQA | 59.3% | 47.1% |
| MMLU Pro | 76.4% | 68.9% |
| HLE | 8.2% | 7.3% |
| LiveCodeBench | 63.1% | 29.5% |
| MATH 500 | 95.7% | 81.7% |
| AIME 2025 | 29.0% | — |
| AIME (Original) | 78.0% | 48.7% |
| SciCode | 35.8% | 22.9% |
| LCR | 25.0% | — |
| IFBench | 38.8% | — |
Key Takeaways
Sonar offers the best value at $0.00/1M, making it ideal for high-volume applications and cost-conscious projects.
QwQ 32B has the strongest reasoning profile with a 45.6 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
QwQ 32B
- Complex reasoning tasks
- Research & analysis
Sonar
- Cost-sensitive applications
- High-volume processing
