Model Comparison
Qwen3 VL 4B Instruct
vs. R1 1776
Comparing 2 AI models · 0 benchmarks · Alibaba, Perplexity
Recommended Pick
PeR1 17762 metric winsStrongest on: Reasoning, Intelligence
Best Reasoning
R1 1776
6.4 reasoning score
Blends available reasoning benchmarks
Differences That Matter
Reasoning gap
R1 1776 leads Qwen3 VL 4B Instruct by 0.7 points on reasoning.
Top-pick rationale
R1 1776 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.
Qwen3 VL 4B Instruct
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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R1 1776
Perplexity
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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Which answer was more useful?
Secure AI Chat made in Europe
Use Claude, ChatGPT, Gemini alongside with EU-Hosted Models like Deepseek, Qwen & Kimi.
EU-hosted inference
Servers in Germany & Finland. Designed to meet strict GDPR and ISO 27001 compliance requirements.
Full Comparison
| Metric | Al Qwen3 VL 4B Instruct | Top Pick Pe R1 1776 |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | — | — |
| Output Cost | — | — |
| Specifications | ||
| Organization | Alibaba | Perplexity |
| Release Date | Oct 14, 2025 | Feb 18, 2025 |
| Performance & Speed | ||
| Throughput | — | — |
| TTFT | — | — |
| Latency | — | — |
| Composite Indices | ||
| Reasoning Score | 5.7 | 6.4 |
| Intelligence | 5.7 | 6.4 |
Key Takeaways
R1 1776 has the strongest reasoning profile with a 6.4 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 VL 4B Instruct
- General-purpose AI
- Versatile applications
R1 1776
- Complex reasoning tasks
- Research & analysis
