Qwen3-VL 8B vs GPT-4.1 mini

	Qwen3-VL 8B	GPT-4.1 mini
Provider	Alibaba Qwen	OpenAI
Model id	`Qwen/Qwen3-VL-8B-Instruct`	`gpt-4.1-mini`
Input price	$0.24 / 1M tokens	$0.40 / 1M tokens
Output price	$0.90 / 1M tokens	$1.60 / 1M tokens
Context window	262K tokens	1M tokens
Capabilities	Vision, Chat, OCR, Tool calling	Chat, Vision, Tool calling, JSON mode
Weights	Open	Closed
Availability	Coming soon	Available
Rate limits	No daily caps; pay per request	Closed-weight.

Cost for 1M input + 1M output tokens

Qwen3-VL 8B

$1.14

GPT-4.1 mini

Qwen3-VL 8B is about 43% cheaper for this workload at list price. Price is only part of it: free tiers and usage tiers cap how much you can send per day, and a retired model is unavailable at any price. The "Rate limits" row above is the practical difference for a production app.

When to pick which

Qwen3-VL 8B — Compact vision-language model for image understanding, OCR and screenshot reasoning.
GPT-4.1 mini — Closed-weight.

Try Qwen3-VL 8B

Same OpenAI request shape; the change is the base URL and key. Full parameters, aliases and pricing on the model page.

curl https://api.inferenceapis.com/v1/chat/completions \
  -H "Authorization: Bearer $INFERENCE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "Qwen/Qwen3-VL-8B-Instruct",
    "messages": [
      {"role": "system", "content": "You are a helpful assistant."},
      {"role": "user", "content": "Hello! What can you do?"}
    ]
  }'

import os
from openai import OpenAI

client = OpenAI(
    base_url="https://api.inferenceapis.com/v1",
    api_key=os.environ["INFERENCE_API_KEY"],
)
response = client.chat.completions.create(
    model="Qwen/Qwen3-VL-8B-Instruct",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Hello! What can you do?"},
    ],
)
print(response.choices[0].message.content)

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.inferenceapis.com/v1",
  apiKey: process.env.INFERENCE_API_KEY,
});
const response = await client.chat.completions.create({
  model: "Qwen/Qwen3-VL-8B-Instruct",
  messages: [
    { role: "system", content: "You are a helpful assistant." },
    { role: "user", content: "Hello! What can you do?" },
  ],
});
console.log(response.choices[0].message.content);

External prices and limits come from the linked provider pages and were verified on 2026-09-16. Spotted a change? Tell us.