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Qwen: Qwen3 VL 30B A3B Instruct
qwen/qwen3-vl-30b-a3b-instructTry Qwen: Qwen3 VL 30B A3B Instruct now
Runs on your balance at the prices above. New accounts start with free usage.
One API. Every model.
Session cost $0.00
Settings
Advanced parameters
Qwen: Qwen3 VL 30B A3B Instruct at a glance
- Input price is 67% lower than the median of 434 Text models.
- Context window of 262,144 tokens, enough for long documents and multi-turn conversations.
- Supports tool (function) calling for agents and integrations.
- Supports structured JSON output with a schema.
- Accepts images as input (vision).
- A typical request (1,000 input / 500 output tokens) costs about $0.00158.
About Qwen: Qwen3 VL 30B A3B Instruct
Qwen3 VL 30B A3B Instruct is a multimodal model from Qwen, released by the provider on 2025-10-06. It belongs to the Qwen3 VL family, and the Instruct variant is tuned for instruction following on general multimodal tasks. On api14 it is listed under the text category, with a knowledge cutoff of 2025-03-31.
The model accepts text and image inputs and returns text. Its context window is 262144 tokens, and the maximum output is 16384 tokens. The provider describes it as unifying strong text generation with visual understanding for images and videos, with particular strength in perception. In practice this means you can send a prompt that mixes written instructions with image content and receive a text response, all within a single very large context.
That combination points to a fairly wide set of practical uses. Document and screenshot understanding, where a user uploads a page or a UI capture and asks questions about it, fits naturally. Image captioning, visual question answering, and extracting structured details from pictures are all reasonable. Because the context window is large, you can include long text alongside images, for example a lengthy specification plus several reference images, without splitting the work across calls. The instruction-tuned behaviour also suits agent-style flows where the model must follow a defined output format.
You call the model through api14's OpenAI-compatible API using the model id "qwen/qwen3-vl-30b-a3b-instruct". Because the interface is OpenAI-compatible, existing clients and SDKs generally work with only the base URL and model id changed. The model supports a broad set of request parameters: frequency_penalty, logit_bias, logprobs, max_tokens, min_p, presence_penalty, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_logprobs and top_p. Tool calling and structured outputs are therefore available if your workflow needs them, and seed plus the sampling controls let you tune determinism and variety.
A few limits are worth keeping in mind. Output is text only, so the model does not generate images. The maximum output of 16384 tokens is well below the 262144 token context window, so very long generations are not possible in one response. If your task is purely text and does not involve images, a text-only model may be a simpler fit. If you need image generation rather than image understanding, this model is not the right choice.
How to call the Qwen: Qwen3 VL 30B A3B Instruct API
- Create an API key in your dashboard.
- Install the official openai SDK for your language.
- Set baseURL to https://api14.com/api/v1 and model to "qwen/qwen3-vl-30b-a3b-instruct".
import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api14.com/api/v1",
apiKey: process.env.API14_API_KEY,
});
const result = await client.chat.completions.create({
"model": "qwen/qwen3-vl-30b-a3b-instruct",
"messages": [
{
"role": "user",
"content": "Explain vector databases in two sentences."
}
]
});
console.log(result.choices[0].message.content);
Supported parameters
frequency_penaltylogit_biaslogprobsmax_tokensmin_ppresence_penaltyrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_logprobstop_pSpecifications
- Context length
- 262,144
- Max output
- 16,384
- Input
- text, image
- Output
- text
- Knowledge cutoff
- 2025-03-31
Requests on api14 · last 7 days
Qwen: Qwen3 VL 30B A3B Instruct: frequently asked questions
- How much does the Qwen: Qwen3 VL 30B A3B Instruct API cost?
- Qwen: Qwen3 VL 30B A3B Instruct costs Input $0.52 / 1M tokens. It is charged from your USD balance only for successful requests; failed requests are free.
- What is the context window of Qwen: Qwen3 VL 30B A3B Instruct?
- Qwen: Qwen3 VL 30B A3B Instruct reads up to 262,144 tokens per request: prompt, history and documents together. It writes up to 16,384 output tokens per response.
- What can Qwen: Qwen3 VL 30B A3B Instruct do?
- Qwen: Qwen3 VL 30B A3B Instruct accepts text, image and returns text. It supports tool calling, structured JSON output.
- How do I call Qwen: Qwen3 VL 30B A3B Instruct from my code?
- Point any OpenAI SDK at https://api14.com/api/v1 and set the model to "qwen/qwen3-vl-30b-a3b-instruct". No other code changes. Copy a ready example from the code panel on this page.
- What are alternatives to Qwen: Qwen3 VL 30B A3B Instruct?
- Comparable Text models at a similar price: MiniMax: MiniMax M3.1 Flash, DeepSeek: DeepSeek V4.1 Flash 1017, LiquidAI: LFM2.5-24B-A2B. Each runs through the same API key, so switching is one string.
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