Which is cheaper, Qwen3.6 Plus or Qwen3 VL 235B A22B Instruct?

Qwen3 VL 235B A22B Instruct is the cheaper of the two: one 1,000-word request costs about 796 toman.

Which one has the larger context window?

Qwen3.6 Plus, with 1,000,000 tokens.

Qwen3.6 Plus vs Qwen3 VL 235B A22B Instruct

Both sit behind the same key and the same code on uttapen — the only thing that changes is the model string, so you can run each of them against your own workload without touching anything else.

Feature	Qwen3.6 Plus	Qwen3 VL 235B A22B Instruct
Provider	Qwen (Alibaba)	Qwen (Alibaba)
Model id	qwen/qwen3.6-plus	qwen/qwen3-vl-235b-a22b-instruct
Context	1,000,000 tokens	262,144 tokens
Max output	65,536 tokens	32,768 tokens
Input / 1M tokens	94,291 toman	60,926 toman
Output / 1M tokens	565,744 toman	551,238 toman
≈ one 1,000-word request	858 toman	796 toman
Input caching	No	29,013 toman / 1M
Image input	Yes	Yes
File input	No	No
Tool calling	Yes	Yes
JSON output	Yes	Yes
Reasoning mode	Yes	No

Which one for what?

Qwen3.6 Plus

Multi-step problems, maths, and tracking down a bug
Whole documents or a codebase in a single request
Reading screenshots, invoices, and scanned forms
Agents that call your own APIs and database

858 toman per 1,000 words · Model page

Qwen3 VL 235B A22B Instruct

Whole documents or a codebase in a single request
Reading screenshots, invoices, and scanned forms
Agents that call your own APIs and database

796 toman per 1,000 words · Model page

Run both with the same code

Swap the model value between the two ids and send the same request twice; what each answer cost comes back in the X-Uttapen-Cost-Toman header.

curl https://api.uttapen.ir/v1/chat/completions \
  -H "Authorization: Bearer sk-up-…" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen/qwen3.6-plus",
    "messages": [{"role": "user", "content": "Introduce yourself in one sentence."}],
    "stream": true
  }'

from openai import OpenAI

client = OpenAI(
    base_url="https://api.uttapen.ir/v1",
    api_key="sk-up-…",
)

stream = client.chat.completions.create(
    model="qwen/qwen3.6-plus",
    messages=[{"role": "user", "content": "Introduce yourself in one sentence."}],
    stream=True,
)
for chunk in stream:
    print(chunk.choices[0].delta.content or "", end="", flush=True)

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.uttapen.ir/v1",
  apiKey: "sk-up-…",
});

const stream = await client.chat.completions.create({
  model: "qwen/qwen3.6-plus",
  messages: [{ role: "user", content: "Introduce yourself in one sentence." }],
  stream: true,
});
for await (const chunk of stream) {
  process.stdout.write(chunk.choices[0]?.delta?.content ?? "");
}

<?php
// composer require openai-php/client guzzlehttp/guzzle
$client = OpenAI::factory()
    ->withBaseUri('https://api.uttapen.ir/v1')
    ->withApiKey('sk-up-…')
    ->make();

$result = $client->chat()->create([
    'model' => 'qwen/qwen3.6-plus',
    'messages' => [['role' => 'user', 'content' => 'Introduce yourself in one sentence.']],
]);
echo $result->choices[0]->message->content;

package main

import (
	"context"
	"fmt"

	"github.com/openai/openai-go"
	"github.com/openai/openai-go/option"
)

func main() {
	client := openai.NewClient(
		option.WithBaseURL("https://api.uttapen.ir/v1"),
		option.WithAPIKey("sk-up-…"),
	)
	resp, err := client.Chat.Completions.New(context.Background(), openai.ChatCompletionNewParams{
		Model:    "qwen/qwen3.6-plus",
		Messages: []openai.ChatCompletionMessageParamUnion{openai.UserMessage("Introduce yourself in one sentence.")},
	})
	if err != nil {
		panic(err)
	}
	fmt.Println(resp.Choices[0].Message.Content)
}

model = "qwen/qwen3-vl-235b-a22b-instruct"

More comparisons: all pairs · model rankings · full catalogue

base_url = https://api.uttapen.ir/v1