Model Comparison
Ring-1T
vs. 30B (high)
Comparing 2 AI models · 10 benchmarks · InclusionAI, Sarvam
Recommended Pick
InRing-1T10 metric winsStrongest on: Input price, Output price, Reasoning
Lowest Price
Ring-1T
$0.00/1M input price
Best Reasoning
Ring-1T
56.7 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
Ring-1T is ∞x cheaper on input tokens than 30B (high).
Reasoning gap
Ring-1T leads 30B (high) by 31.0 points on reasoning.
Top-pick rationale
Ring-1T wins 10 measurable categories, including Input price, Output price, Reasoning, Intelligence.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
Ring-1T
InclusionAI
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
30B (high)
Sarvam
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Which answer was more useful?
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Full Comparison
| Metric | Top Pick In Ring-1T | 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 | InclusionAI | Sarvam |
| Release Date | Oct 13, 2025 | Mar 6, 2026 |
| Performance & Speed | ||
| Throughput | — | — |
| TTFT | — | — |
| Latency | — | — |
| Composite Indices | ||
| Value Score | — | 100.0 |
| Reasoning Score | 56.7 | 25.7 |
| Intelligence | 16.3 | 6.4 |
| Math | 89.3 | — |
| Standard Benchmarks | ||
| GPQA | 77.4% | 63.3% |
| MMLU Pro | 80.6% | — |
| HLE | 11.1% | 7.5% |
| LiveCodeBench | 64.3% | — |
| AIME 2025 | 89.3% | — |
| SciCode | 36.7% | 19.2% |
| LCR | 53.3% | 0.0% |
| IFBench | 44.6% | 26.5% |
| TAU-bench v2 | 26.3% | 34.5% |
| TerminalBench Hard | 6.8% | 2.3% |
Key Takeaways
Ring-1T offers the best value at $0.00/1M,making it ideal for high-volume applications and cost-conscious projects.
Ring-1T has the strongest reasoning profile with a 56.7 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
Ring-1T
- Cost-sensitive applications
- High-volume processing
- Complex reasoning tasks
- Research & analysis
30B (high)
- General-purpose AI
- Versatile applications
