Model Comparison
Qwen3 1.7B (Non-reasoning)
vs. Ring-1T
Comparing 2 AI models · 12 benchmarks · Alibaba, InclusionAI
Recommended Pick
InRing-1T13 metric winsStrongest on: Reasoning, Intelligence, Math
Lowest Price
Qwen3 1.7B (Non-reasoning)
$0.00/1M input price
Best Reasoning
Ring-1T
56.5 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
Ring-1T leads Qwen3 1.7B (Non-reasoning) by 37.8 points on reasoning.
Top-pick rationale
Ring-1T wins 13 measurable categories, including Reasoning, Intelligence, Math, GPQA.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
Qwen3 1.7B (Non-reasoning)
Alibaba
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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Ring-1T
InclusionAI
TTFT
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Time
—
tok/s
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Tokens
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Cost
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Which answer was more useful?
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Full Comparison
| Metric | Al Qwen3 1.7B (Non-reasoning) | Top Pick In Ring-1T |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.00/1M | $0.00/1M |
| Output Cost | $0.00/1M | $0.00/1M |
| Specifications | ||
| Organization | Alibaba | InclusionAI |
| Release Date | Apr 28, 2025 | Oct 13, 2025 |
| Performance & Speed | ||
| Throughput | — | — |
| TTFT | — | — |
| Latency | — | — |
| Composite Indices | ||
| Reasoning Score | 18.7 | 56.5 |
| Intelligence | 1.5 | 16.2 |
| Math | 7.3 | 89.3 |
| Standard Benchmarks | ||
| GPQA | 28.3% | 77.4% |
| MMLU Pro | 41.1% | 80.6% |
| HLE | 5.2% | 10.2% |
| LiveCodeBench | 12.6% | 64.3% |
| MATH 500 | 71.7% | — |
| AIME 2025 | 7.3% | 89.3% |
| AIME (Original) | 9.7% | — |
| SciCode | 6.9% | 36.7% |
| LCR | 0.0% | 45.7% |
| IFBench | 21.1% | 44.6% |
| TAU-bench v2 | 21.6% | 26.3% |
| TerminalBench Hard | 0.0% | 6.8% |
Key Takeaways
Qwen3 1.7B (Non-reasoning) 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 56.5 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
Qwen3 1.7B (Non-reasoning)
- Cost-sensitive applications
- High-volume processing
Ring-1T
- Complex reasoning tasks
- Research & analysis
