LangMart: Qwen: Qwen3 14B
Model Overview
| Property | Value |
|---|---|
| Model ID | openrouter/qwen/qwen3-14b |
| Name | Qwen: Qwen3 14B |
| Provider | qwen |
| Released | 2025-04-28 |
Description
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 logical inference, and a "non-thinking" mode for general-purpose conversation. The model is fine-tuned for instruction-following, agent tool use, creative writing, and multilingual tasks across 100+ languages and dialects. It natively handles 32K token contexts and can extend to 131K tokens using YaRN-based scaling.
Description
LangMart: Qwen: Qwen3 14B is a language model provided by qwen. This model offers advanced capabilities for natural language processing tasks.
Provider
qwen
Specifications
| Spec | Value |
|---|---|
| Context Window | 40,960 tokens |
| Modalities | text->text |
| Input Modalities | text |
| Output Modalities | text |
Pricing
| Type | Price |
|---|---|
| Input | $0.05 per 1M tokens |
| Output | $0.22 per 1M tokens |
Capabilities
- Frequency penalty
- Include reasoning
- Max tokens
- Min p
- Presence penalty
- Reasoning
- Repetition penalty
- Response format
- Seed
- Stop
- Structured outputs
- Temperature
- Tool choice
- Tools
- Top k
- Top p
Detailed Analysis
Qwen3-14B is a standard-size model in the Qwen 3 series, offering enhanced capabilities over the 8B model with reasonable computational requirements. Released April 2025. Key characteristics: (1) Architecture: 14B parameter dense transformer achieving performance comparable to Qwen2.5-32B through Qwen 3 architectural improvements and extensive 36T token training; demonstrates efficiency gains from next-generation architecture; (2) Performance: Strong results across reasoning, coding, mathematics, and long-context understanding benchmarks; competitive with commercial models in the GPT-3.5-Turbo to GPT-4 range on many tasks; (3) Use Cases: Production applications requiring enhanced capability over 8B models, complex reasoning tasks, advanced code generation, sophisticated content creation, research applications, multi-turn conversations requiring deeper understanding; (4) Context Window: 131K tokens supporting comprehensive document analysis and long-form generation; (5) Pricing: Mid-tier pricing reflecting 14B scale - more expensive than 8B but significantly cheaper than 32B/235B models; (6) Trade-offs: Good middle ground between efficiency (vs 32B+) and capability (vs 4B/8B). Best for applications where 8B models are insufficient but the full computational cost of 32B+ models is not warranted. Strong choice for production workloads requiring enhanced reasoning and understanding.