Model Comparison
OLMo 2 7B
vs. 30B (high)
Comparing 2 AI models · 10 benchmarks · Allen Institute for AI, Sarvam
Recommended Pick
Sa30B (high)9 metric winsStrongest on: Throughput, Reasoning, Intelligence
Lowest Price
OLMo 2 7B
$0.00/1M input price
Best Reasoning
30B (high)
25.6 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
OLMo 2 7B is ∞x cheaper on input tokens than 30B (high).
Reasoning gap
30B (high) leads OLMo 2 7B by 17.7 points on reasoning.
Top-pick rationale
30B (high) wins 9 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.
OLMo 2 7B
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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30B (high)
Sarvam
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Which answer was more useful?
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Full Comparison
| Metric | Al OLMo 2 7B | Top Pick Sa 30B (high) |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.00/1M | $0.03/1M |
| Output Cost | $0.00/1M | $0.11/1M |
| Blended (3:1) | — | $0.05/1M |
| Specifications | ||
| Organization | Allen Institute for AI | Sarvam |
| Release Date | Nov 26, 2024 | Mar 6, 2026 |
| Performance & Speed | ||
| Throughput | — | 221.1 tok/s |
| TTFT | — | 1134ms |
| Latency | — | 10180ms |
| Composite Indices | ||
| Value Score | — | 100.0 |
| Reasoning Score | 7.9 | 25.6 |
| Intelligence | 3.9 | 6.6 |
| Math | 0.7 | — |
| Standard Benchmarks | ||
| GPQA | 28.8% | 63.3% |
| MMLU Pro | 28.2% | — |
| HLE | 5.5% | 7.0% |
| LiveCodeBench | 4.1% | — |
| AIME 2025 | 0.7% | — |
| SciCode | 3.7% | 19.2% |
| LCR | 0.0% | 0.0% |
| IFBench | 24.4% | 26.5% |
| TAU-bench v2 | 0.0% | 34.5% |
| TerminalBench Hard | 0.0% | 2.3% |
Key Takeaways
OLMo 2 7B offers the best value at $0.00/1M,making it ideal for high-volume applications and cost-conscious projects.
30B (high) has the strongest reasoning profile with a 25.6 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
OLMo 2 7B
- Cost-sensitive applications
- High-volume processing
30B (high)
- Complex reasoning tasks
- Research & analysis
