Model Comparison
OLMo 2 7B
vs. PALM-2
Comparing 2 AI models · 10 benchmarks · Allen Institute for AI, Google
Recommended Pick
AlOLMo 2 7B2 metric winsStrongest on: Reasoning, Intelligence
Lowest Price
OLMo 2 7B
$0.00/1M input price
Best Reasoning
OLMo 2 7B
7.9 reasoning score
Blends available reasoning benchmarks
Best for Coding
PALM-2
4.6 coding index
Composite Indices
Higher is better; speed and price are normalized
Standard Benchmarks
Only benchmarks with data are shown
Differences That Matter
Reasoning gap
OLMo 2 7B leads PALM-2 by 4.7 points on reasoning.
Top-pick rationale
OLMo 2 7B wins 2 measurable categories, including Reasoning, Intelligence.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
OLMo 2 7B
Allen Institute for AI
TTFT
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Time
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tok/s
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Tokens
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Cost
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PALM-2
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
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Which answer was more useful?
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Full Comparison
| Metric | Top Pick Al OLMo 2 7B | Go PALM-2 |
|---|---|---|
| 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 | |
| Release Date | Nov 26, 2024 | May 10, 2023 |
| Performance & Speed | ||
| Throughput | — | — |
| TTFT | — | — |
| Latency | — | — |
| Composite Indices | ||
| Reasoning Score | 7.9 | 3.2 |
| Intelligence | 3.9 | 3.2 |
| Coding | — | 4.6 |
| Math | 0.7 | — |
| Standard Benchmarks | ||
| GPQA | 28.8% | — |
| MMLU Pro | 28.2% | — |
| HLE | 5.5% | — |
| LiveCodeBench | 4.1% | — |
| AIME 2025 | 0.7% | — |
| SciCode | 3.7% | — |
| LCR | 0.0% | — |
| IFBench | 24.4% | — |
| TAU-bench v2 | 0.0% | — |
| TerminalBench Hard | 0.0% | — |
Key Takeaways
OLMo 2 7B offers the best value at $0.00/1M,making it ideal for high-volume applications and cost-conscious projects.
OLMo 2 7B has the strongest reasoning profile with a 7.9 reasoning score,combining the available reasoning-heavy benchmarks.
PALM-2 reaches a 4.6 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
OLMo 2 7B
- Cost-sensitive applications
- High-volume processing
- Complex reasoning tasks
- Research & analysis
PALM-2
- Code generation
- Software development
