Gemma 3n E4B-it is optimized for efficient execution on mobile and low-resource devices, such as phones, laptops, and tablets. It supports multimodal inputs—including text, visual data, and audio—enabling diverse tasks such as text generati…
Model details →Google: Gemma 3n 4B vs Qwen: Qwen3 14B
Qwen: Qwen3 14B wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.
Qwen3-14B is a dense 14.8B parameter causal language model from the Qwen3 series, designed for both complex reasoning and efficient dialogue. It supports seamless switching between a "thinking" mode for tasks like math, programming, and log…
Model details →Side-by-side comparison
| Capability | Google: Gemma 3n 4B | Qwen: Qwen3 14B | Winner |
|---|---|---|---|
| Context window Maximum number of input tokens the model can attend to in a single request. | 33K | 41K | 🏆 Qwen: Qwen3 14B |
| Input price (per 1M) Cost per million input tokens billed by the provider. | $0.02 | $0.06 | 🏆 Google: Gemma 3n 4B |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $0.04 | $0.24 | 🏆 Google: Gemma 3n 4B |
| Tool / function calling First-class support for emitting structured tool calls. | — | Yes | 🏆 Qwen: Qwen3 14B |
| Vision input Accepts image inputs alongside text. | — | — | Tie |
| Reasoning mode Internal chain-of-thought / extended-thinking support. | — | Yes | 🏆 Qwen: Qwen3 14B |
Frequently asked questions
Is Google: Gemma 3n 4B better than Qwen: Qwen3 14B?
Qwen: Qwen3 14B wins on 3 of 6 axes — pricing and capability skew in its favour for most workloads.
What's the price difference between Google: Gemma 3n 4B and Qwen: Qwen3 14B?
Input: $0.02 vs $0.06 per 1M tokens. Output: $0.04 vs $0.24 per 1M tokens.
What context windows do Google: Gemma 3n 4B and Qwen: Qwen3 14B support?
Google: Gemma 3n 4B supports up to 33K tokens. Qwen: Qwen3 14B supports up to 41K tokens.
Do both Google: Gemma 3n 4B and Qwen: Qwen3 14B support tool calling?
Google: Gemma 3n 4B: not advertised. Qwen: Qwen3 14B: yes.