LightweightAlibaba

Qwen 3 14B

Qwen 3 14B is Alibaba's lightweight text model with a 40K token context window, optimized for speed with 63.57 tokens per second output.

Context 41K
Tier Lightweight
Input from
$0.060 / 1M tokens
across 2 providers

API Pricing

Cheapest on OpenRouter 33% below avg
ProviderInput / 1MOutput / 1MSpeedTTFTUpdated
$0.060$0.24066.0 t/s1.0s4/14/2026
$0.120$0.24066.0 t/s1.0s4/4/2026

Prices updated daily. Last check: 4/14/2026

Model Details

General

Creator
Alibaba
Family
Qwen
Tier
Lightweight
Context Window
41K
Modalities
Text

Capabilities

Tool Calling
No
Open Source
No

Strengths & Limitations

  • Fast output generation at 63.57 tokens per second
  • Moderate time to first token at 955 milliseconds for responsive applications
  • 40K token context window supports substantial document processing
  • Lightweight architecture enables efficient deployment and scaling
  • 14B parameter size balances capability with computational requirements
  • Part of established Qwen model family with proven track record
  • Optimized for text-focused applications without multimodal complexity
  • No tool calling or function execution capabilities
  • Limited to text-only processing without vision or audio support
  • Proprietary model with no open source availability
  • Smaller parameter count compared to flagship models in the family
  • Lightweight tier positioning limits complex reasoning capabilities

Key Features

40,960 token context window
Text-only input and output processing
63.57 tokens per second output speed
955ms time to first token
14 billion parameter architecture
Streaming response support
Lightweight inference optimization
API-based deployment model

About Qwen 3 14B

Qwen 3 14B is a lightweight text generation model developed by Alibaba as part of the Qwen family. This 14-billion parameter model sits in the lightweight tier, designed for applications requiring fast inference speeds while maintaining reasonable performance across general language tasks. The model features a 40,960 token context window and focuses exclusively on text processing, without support for additional modalities like vision or audio. Benchmark data shows strong performance characteristics with an output speed of 63.57 tokens per second and a time to first token of 955 milliseconds, indicating optimization for responsive applications. Qwen 3 14B targets use cases where speed and efficiency are prioritized over maximum capability, making it suitable for production environments requiring quick responses at scale. Its positioning as a lightweight model distinguishes it from larger, more computationally intensive models in scenarios where the additional capability may not justify the performance cost.

Common Use Cases

Qwen 3 14B is designed for applications requiring fast, efficient text generation where speed takes precedence over maximum capability. Its 63.57 tokens per second output rate makes it well-suited for real-time chat applications, content generation pipelines, and high-volume text processing tasks. The 40K context window enables document summarization, content analysis, and multi-turn conversations while maintaining quick response times. Organizations building customer service bots, content moderation systems, or text classification services can leverage its lightweight architecture for cost-effective scaling without sacrificing reasonable language understanding and generation quality.

Frequently Asked Questions

How much does Qwen 3 14B cost per million tokens?

Qwen 3 14B pricing varies by provider and pricing type (standard vs batch). Check the pricing table above for current rates across all providers.

What is Qwen 3 14B best used for?

Qwen 3 14B excels at fast text generation tasks where speed is prioritized, including real-time chat applications, high-volume content processing, document summarization within its 40K context window, and production systems requiring quick response times with reasonable language quality.

Does Qwen 3 14B support function calling or multimodal inputs?

No, Qwen 3 14B is focused on text-only processing and does not support function calling, tool use, or multimodal inputs like images or audio. It's designed as a lightweight model optimized for fast text generation tasks.