Model Comparison
Qwen2.5 Turbo
vs. R1 1776
Comparing 2 AI models · 7 benchmarks · Alibaba, Perplexity
Recommended Pick
PeR1 17766 metric winsStrongest on: Input price, Output price, TTFT
Lowest Price
R1 1776
$0.00/1M input price
Best Reasoning
R1 1776
50.8 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
Price gap
R1 1776 is ∞x cheaper on input tokens than Qwen2.5 Turbo.
Reasoning gap
R1 1776 leads Qwen2.5 Turbo by 22.0 points on reasoning.
Top-pick rationale
R1 1776 wins 6 measurable categories, including Input price, Output price, TTFT, Latency.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
Qwen2.5 Turbo
Alibaba
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
R1 1776
Perplexity
TTFT
—
Time
—
tok/s
—
Tokens
—
Cost
—
Which answer was more useful?
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Full Comparison
| Metric | Al Qwen2.5 Turbo | Top Pick Pe R1 1776 |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.05/1M | $0.00/1M |
| Output Cost | $0.20/1M | $0.00/1M |
| Blended (3:1) | $0.09/1M | — |
| Specifications | ||
| Organization | Alibaba | Perplexity |
| Release Date | Nov 18, 2024 | Feb 18, 2025 |
| Performance & Speed | ||
| Throughput | 114.7 tok/s | — |
| TTFT | 1102ms | — |
| Latency | 1102ms | — |
| Composite Indices | ||
| Value Score | 100.0 | — |
| Reasoning Score | 28.8 | 50.8 |
| Intelligence | 6.3 | 6.3 |
| Standard Benchmarks | ||
| GPQA | 41.0% | — |
| MMLU Pro | 63.3% | — |
| HLE | 4.2% | — |
| LiveCodeBench | 16.3% | — |
| MATH 500 | 80.5% | 95.4% |
| AIME (Original) | 12.0% | — |
| SciCode | 15.3% | — |
Key Takeaways
R1 1776 offers the best value at $0.00/1M,making it ideal for high-volume applications and cost-conscious projects.
R1 1776 has the strongest reasoning profile with a 50.8 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
Qwen2.5 Turbo
- General-purpose AI
- Versatile applications
R1 1776
- Cost-sensitive applications
- High-volume processing
- Complex reasoning tasks
- Research & analysis
