Qwen3 14B
Open weightToolsQwen · Released April 2025 · Knowledge cutoff March 2025
Qwen3-14B is a dense 14.8B parameter causal language model from the Qwen3 series, designed for both complex reasoning and efficient dialogue.
It is part of Alibaba's Qwen family, a broad catalog where Max leads on capability and Max Prime serves it at higher throughput, Plus balances cost, and Flash, VL and the open-weight sizes cover high-volume, vision and self-hosted work.
Facts and pricing
- Provider
- Qwen
- Context window
- 41K tokens
- Input price
- 1.4 credits / 1M tokens ($0.12 raw)
- Output price
- 2.9 credits / 1M tokens ($0.24 raw)
- Vision (image input)
- No
- Tool calling
- Yes
- Extended reasoning
- No
Credits are what Zeplik bills: 1 credit = $0.10, computed from the raw provider rate with a 1.20x margin. Raw prices shown per 1M tokens.
Try Qwen3 14B now
What Qwen3 14B is best for
- Everyday chat and drafting on an open-weight model with transparent lineage
- Tool use and agents: reliably calls functions, so it can search, run skills and drive workflows
Example prompts
Prompts that suit a open weight model like Qwen3 14B:
- Draft a project update from these rough notes
- Explain how HTTPS works to a curious teenager
- Turn this list of features into a changelog entry
- Brainstorm objections to this proposal and how to answer them
Qwen family
| Model | Context | Input cr/M | Output cr/M | Released |
|---|---|---|---|---|
| Qwen3.8 Max Prime | 1M | 48.0 | 144 | September 2026 |
| Qwen3.8 Omni Flash | 1M | 1.8 | 5.6 | September 2026 |
| Qwen3.8 Max (0902) | 1M | 24.0 | 72.0 | September 2026 |
| Qwen3.8 Flash | 1M | 1.8 | 5.6 | August 2026 |
| Qwen3.8 27B | 262K | 1.8 | 22.5 | August 2026 |
| Qwen3.8 2.4T A95B | 1M | 24.0 | 72.0 | August 2026 |
| Qwen3.7 Flash | 1M | 0.36 | 1.6 | July 2026 |
| Qwen3.7 Plus | 1M | 3.8 | 15.4 | June 2026 |
| Qwen3.7 Max | 1M | 17.7 | 53.1 | May 2026 |
| Qwen3.5 Plus 2026-04-20 | 1M | 3.6 | 21.6 | April 2026 |
Model comparisons
- Llama 4 Maverick vs Qwen3.7 Max
- DeepSeek V4 Pro 0423 vs Qwen3.7 Max
- Qwen3.7 Max vs GLM 5.2
- Qwen3.7 Max vs Qwen3.7 Plus
Frequently asked questions
- What is Qwen3 14B?
- Qwen3 14B is an AI model by Qwen. Qwen3-14B is a dense 14.8B parameter causal language model from the Qwen3 series, designed for both complex reasoning and efficient dialogue.
- How much does Qwen3 14B cost on Zeplik?
- Input tokens cost 1.4 credits per million and output tokens 2.9 credits per million (1 credit = $0.10; the raw provider rates are $0.12 and $0.24 per million). New accounts start with free credits.
- How long can a conversation with Qwen3 14B be?
- Qwen3 14B has a 41K-token context window (40,960 tokens), which covers the conversation plus any documents you attach.
- Does Qwen3 14B support images and tools?
- Qwen3 14B is text-only and supports tool calling.
Related models
Qwen3.8 Max Prime is a higher-throughput variant of Qwen3.8 Max from Alibaba's Qwen team, served as a separate SKU at a higher price point.
Qwen3.8 Omni Flash is an omni-modal reasoning model from Alibaba, the first Qwen model built around agentic capabilities with native audio-video understanding.
Qwen3.8 Max 0902 is an updated snapshot of Qwen3.8 Max from Alibaba's Qwen team.
Qwen3.8 Flash is a multimodal reasoning model from Alibaba. It is suited for coding assistance, agentic workflows, visual understanding, document and codebase analysis, desktop interaction, chart analysis, and long-video analysis.
Qwen3.8 27B is an open-weight dense vision-language model from Qwen.
Qwen3.8 2.4T A95B is an open-weight sparse mixture-of-experts model from Qwen and the open-weight variant of [Qwen3.8 Max](/qwen/qwen3.8-max), with 95 billion active parameters out of 2.4 trillion total.
More you can do with Qwen3 14B
- 468 AI skillsReady-to-run expert methods for writing, data, code and more, each running on Qwen3 14B or any model you pick.
- 997 integrationsConnect Gmail, Slack, GitHub, Notion and hundreds more so the assistant can work in your apps.
- Simple pricingPlus, Pro and Max plans with a monthly credit allowance that works across every model.