DeepSeek-V3.1 is a large hybrid reasoning model (671B parameters, 37B active) that supports both thinking and non-thinking modes via prompt templates. It extends the DeepSeek-V3 base with a two-phase long-context training process, reaching …
Model details →DeepSeek: DeepSeek V3.1 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 | DeepSeek: DeepSeek V3.1 | 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. | $0.15 | $0.06 | 🏆 Qwen: Qwen3 14B |
| Output price (per 1M) Cost per million output tokens billed by the provider. | $0.75 | $0.24 | 🏆 Qwen: Qwen3 14B |
| Tool / function calling First-class support for emitting structured tool calls. | Yes | Yes | Tie |
| Vision input Accepts image inputs alongside text. | — | — | Tie |
| Reasoning mode Internal chain-of-thought / extended-thinking support. | Yes | Yes | Tie |
Frequently asked questions
Is DeepSeek: DeepSeek V3.1 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 DeepSeek: DeepSeek V3.1 and Qwen: Qwen3 14B?
Input: $0.15 vs $0.06 per 1M tokens. Output: $0.75 vs $0.24 per 1M tokens.
What context windows do DeepSeek: DeepSeek V3.1 and Qwen: Qwen3 14B support?
DeepSeek: DeepSeek V3.1 supports up to 33K tokens. Qwen: Qwen3 14B supports up to 41K tokens.
Do both DeepSeek: DeepSeek V3.1 and Qwen: Qwen3 14B support tool calling?
DeepSeek: DeepSeek V3.1: yes. Qwen: Qwen3 14B: yes.