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Qwen: Qwen3 VL 8B Instruct
qwen/qwen3-vl-8b-instructTry Qwen: Qwen3 VL 8B 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 8B Instruct at a glance
- Input price is 44% 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 $0.00219.
About Qwen: Qwen3 VL 8B Instruct
Qwen: Qwen3 VL 8B Instruct is a multimodal vision-language model from the Qwen3-VL series, made by Qwen. It was released by the provider on 2025-10-14. The model belongs to the text category on api14, and its design centres on high-fidelity understanding and reasoning across text, images, and video, with improved multimodal fusion using Interleaved-MRoPE for long-horizon tasks.
The model accepts image and text as inputs and returns text. Its context window is 262,144 tokens, and the maximum output is 235,929 tokens. That combination of a large context and a large output budget means you can supply long documents or many images alongside your instructions and still leave room for a substantial generated response. Because the output modality is text only, the model is suited to tasks where the answer is written language rather than generated media.
Practical uses follow directly from those capabilities. You can send an image together with a question and get a text answer, which fits document and screenshot understanding, extracting information from scanned or photographed material, and describing or reasoning about visual content. Since video is part of the model's stated scope, it can also be applied to tasks that involve reasoning over video input. The long context supports multi-image or long-document workflows where the model needs to consider a lot of material at once before producing its answer.
You call the model through api14's OpenAI-compatible API using the model id "qwen/qwen3-vl-8b-instruct". The supported request parameters are frequency_penalty, logit_bias, logprobs, max_tokens, 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 both available, so you can wire the model into function-calling flows or constrain its output to a schema. Sampling behaviour can be tuned with temperature, top_p, and top_k, while seed, stop, and the penalty parameters give you further control over determinism and repetition.
If your task is text only and does not involve images or video, the vision capability is not doing any work for you, and a text-only model may be a simpler fit. The same applies if you need an output modality other than text, since this model returns text only.
How to call the Qwen: Qwen3 VL 8B 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-8b-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-8b-instruct",
"messages": [
{
"role": "user",
"content": "Explain vector databases in two sentences."
}
]
});
console.log(result.choices[0].message.content);
Supported parameters
frequency_penaltylogit_biaslogprobsmax_tokenspresence_penaltyrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_logprobstop_pSpecifications
- Context length
- 262,144
- Max output
- 235,929
- Input
- image, text
- Output
- text
Requests on api14 · last 7 days
Qwen: Qwen3 VL 8B Instruct: frequently asked questions
- How much does the Qwen: Qwen3 VL 8B Instruct API cost?
- Qwen: Qwen3 VL 8B Instruct costs Input $0.88 / 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 8B Instruct?
- Qwen: Qwen3 VL 8B Instruct reads up to 262,144 tokens per request: prompt, history and documents together. It writes up to 235,929 output tokens per response.
- What can Qwen: Qwen3 VL 8B Instruct do?
- Qwen: Qwen3 VL 8B Instruct accepts image, text and returns text. It supports tool calling, structured JSON output.
- How do I call Qwen: Qwen3 VL 8B Instruct from my code?
- Point any OpenAI SDK at https://api14.com/api/v1 and set the model to "qwen/qwen3-vl-8b-instruct". No other code changes. Copy a ready example from the code panel on this page.
- What are alternatives to Qwen: Qwen3 VL 8B Instruct?
- Comparable Text models at a similar price: Inception: Mercury 2, Mistral: Mistral Large 3 2512 (batch), OpenAI: GPT-4.1 Mini (batch). Each runs through the same API key, so switching is one string.
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