Model Comparison
R1 Distill Qwen 14B
vs. Gemma 4 E4B (Non-reasoning)
Comparing 2 AI models · 12 benchmarks · DeepSeek, Google
Recommended Pick
Go Gemma 4 E4B (Non-reasoning) 4 metric wins Strongest on: GPQA, HLE, LCR
Lowest Price
R1 Distill Qwen 14B
$0.00/1M input price
Best Reasoning
R1 Distill Qwen 14B
47.9 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
R1 Distill Qwen 14B leads Gemma 4 E4B (Non-reasoning) by 25.1 points on reasoning.
Top-pick rationale
Gemma 4 E4B (Non-reasoning) wins 4 measurable categories, including GPQA, HLE, LCR, IFBench.
Response Face-Off
Run one prompt through the selected models and compare response quality with live speed and cost context.
R1 Distill Qwen 14B
DeepSeek
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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Gemma 4 E4B (Non-reasoning)
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?
Chat with leading AI models
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Full Comparison
| Metric | De R1 Distill Qwen 14B | Top Pick Go Gemma 4 E4B (Non-reasoning) |
|---|---|---|
| Pricing per 1M tokens | ||
| Input Cost | $0.00/1M | $0.00/1M |
| Output Cost | $0.00/1M | $0.00/1M |
| Specifications | ||
| Organization | DeepSeek | |
| Release Date | Jan 20, 2025 | Apr 3, 2026 |
| Performance & Speed | ||
| Throughput | — | — |
| TTFT | — | — |
| Latency | — | — |
| Composite Indices | ||
| Reasoning Score | 47.9 | 22.8 |
| Intelligence | 9.8 | 8.9 |
| Math | 55.7 | — |
| Standard Benchmarks | ||
| GPQA | 48.4% | 54.9% |
| MMLU Pro | 74.0% | — |
| HLE | 4.4% | 4.7% |
| LiveCodeBench | 37.6% | — |
| MATH 500 | 94.9% | — |
| AIME 2025 | 55.7% | — |
| AIME (Original) | 66.7% | — |
| SciCode | 23.9% | 3.9% |
| LCR | 7.0% | 18.0% |
| IFBench | 22.1% | 40.5% |
| TAU-bench v2 | — | 26.0% |
| TerminalBench Hard | — | 7.6% |
Key Takeaways
R1 Distill Qwen 14B offers the best value at $0.00/1M, making it ideal for high-volume applications and cost-conscious projects.
R1 Distill Qwen 14B has the strongest reasoning profile with a 47.9 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
R1 Distill Qwen 14B
- Cost-sensitive applications
- High-volume processing
- Complex reasoning tasks
- Research & analysis
Gemma 4 E4B (Non-reasoning)
- General-purpose AI
- Versatile applications
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