qwen3-14b
Qwen3-14B is a dense 14.8B-parameter model from the Qwen3 series for complex reasoning and efficient dialogue, switching between thinking and non-thinking modes.
Pricing: Input 24 credits / 1M tokens (≈ $0.12), Output 48 credits / 1M tokens (≈ $0.24).
Prices updated
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Qwen3 14B API on ModelFold
Qwen3-14B is a dense 14.8B-parameter model from the Qwen3 series for complex reasoning and efficient dialogue, switching between thinking and non-thinking modes. Try Qwen3 14B in the ModelFold Playground, then call it from your own code through an OpenAI-compatible chat completions API.
What Is the Qwen3 14B API
Qwen3 14B at a glance
Qwen3 14B is a chat model from Qwen. It accepts text as input and returns text, with a context window of up to 41K tokens.
Use it without hosting anything
On ModelFold you call Qwen3 14B with a single API key — no model weights to download and no inference servers to run. The same key also works for the other chat, image, video and audio models on ModelFold.
Core Capabilities of Qwen3 14B
Up to 41K tokens of context
Keep long conversations, large documents and sizeable code in a single request, so the model can reason over the full material instead of fragments.
Function calling
Qwen3 14B supports tool (function) calling: describe your functions in the request and the model returns structured calls your code can run — the basis for agents and integrations.
Reasoning mode
Qwen3 14B can produce reasoning before its final answer; in the Playground you can switch reasoning on or off to compare results.
Structured outputs
Ask for JSON that follows a schema (response_format), which makes extraction, classification and system integrations more reliable.
How to Use Qwen3 14B on ModelFold
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Step 1: Try it in the Playground
Open the Playground at the top of this page, type a prompt and see how Qwen3 14B responds before writing any code.
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Step 2: Create an API key
Sign in to ModelFold and create an API key in the console. Keep it secret and send it as a Bearer token.
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Step 3: Send a request
Call POST https://modelfold.ai/v1/chat/completions with "model": "qwen3-14b" and your messages. Existing OpenAI-compatible SDKs work by changing the base URL and key.
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Step 4: Ship and monitor
Integrate the response into your product and check token usage and spend for every call in the console logs.
What You Can Build with Qwen3 14B
High-volume pipelines
Run classification, extraction, rewriting and batch jobs at scale where cost per request matters.
Analysis and complex reasoning
Work through research questions, data interpretation, planning and other problems that need careful step-by-step reasoning.
Multilingual products
Serve users in many languages with translation, localized support replies and cross-language search.
Writing and content
Draft, edit and translate articles, emails, product copy and documentation in a consistent tone.
Frequently Asked Questions
What is Qwen3 14B?⌄
Qwen3-14B is a dense 14.8B-parameter model from the Qwen3 series for complex reasoning and efficient dialogue, switching between thinking and non-thinking modes.
Which inputs does Qwen3 14B support?⌄
Qwen3 14B accepts text and returns text. Through ModelFold you send text messages; documents attached in the Playground are converted to text.
How long is the context window of Qwen3 14B?⌄
Up to 41K tokens, shared between your input and the model’s output.
Does Qwen3 14B support function calling?⌄
Yes. Qwen3 14B supports tools / function calling through the standard tools parameter of the chat completions API.
How is Qwen3 14B billed on ModelFold?⌄
Pay as you go by tokens: input and output tokens are charged at the per-million-token prices shown on this page. There is no monthly fee, and failed requests are not charged.
How do I call Qwen3 14B through the API?⌄
Send a POST request to https://modelfold.ai/v1/chat/completions with "model": "qwen3-14b", using your ModelFold API key as the Bearer token.
| Input | 24 credits 1M tokens≈ $0.12 |
| Output | 48 credits 1M tokens≈ $0.24 |
Billed per token: input and output are priced separately, and thinking tokens count as output. The Playground charges exactly the same way.
Read API docs →AI Agents · Claude Code / Cursor / Trae →curl https://modelfold.ai/v1/chat/completions \
-H "Authorization: Bearer $MODELFOLD_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"qwen3-14b","messages":[{"role":"user","content":"Hello"}]}'