Model Comparison
OLMo 2 32B
vs. Sonar Reasoning
Comparing 2 AI models · 12 benchmarks · Allen Institute for AI, Perplexity
Recommended Pick
PeSonar Reasoning3 metric winsStrongest on: Reasoning, Intelligence, GPQA
Lowest Price
OLMo 2 32B
$0.00/1M input price
Best Reasoning
Sonar Reasoning
60.8 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
Reasoning gap
Sonar Reasoning leads OLMo 2 32B by 51.2 points on reasoning.
Top-pick rationale
Sonar Reasoning wins 3 measurable categories, including Reasoning, Intelligence, GPQA.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
OLMo 2 32B
Allen Institute for AI
TTFT
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Time
—
tok/s
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Tokens
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Cost
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Sonar Reasoning
Perplexity
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Which answer was more useful?
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Full Comparison
| Metric | Al OLMo 2 32B | Top Pick Pe Sonar Reasoning |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.00/1M | $0.00/1M |
| Output Cost | $0.00/1M | $0.00/1M |
| Specifications | ||
| Organization | Allen Institute for AI | Perplexity |
| Release Date | Mar 13, 2025 | Jan 28, 2025 |
| Performance & Speed | ||
| Throughput | — | — |
| TTFT | — | — |
| Latency | — | — |
| Composite Indices | ||
| Reasoning Score | 9.6 | 60.8 |
| Intelligence | 5.0 | 11.7 |
| Math | 3.3 | — |
| Standard Benchmarks | ||
| GPQA | 32.8% | 62.3% |
| MMLU Pro | 51.1% | — |
| HLE | 3.7% | — |
| LiveCodeBench | 6.8% | — |
| MATH 500 | — | 92.1% |
| AIME 2025 | 3.3% | — |
| AIME (Original) | — | 77.0% |
| SciCode | 8.0% | — |
| LCR | 0.0% | — |
| IFBench | 38.1% | — |
| TAU-bench v2 | 0.0% | — |
| TerminalBench Hard | 0.0% | — |
Key Takeaways
OLMo 2 32B offers the best value at $0.00/1M,making it ideal for high-volume applications and cost-conscious projects.
Sonar Reasoning has the strongest reasoning profile with a 60.8 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
OLMo 2 32B
- Cost-sensitive applications
- High-volume processing
Sonar Reasoning
- Complex reasoning tasks
- Research & analysis
