Which is cheaper, Qwen3.7 Max or Qwen3 VL 235B A22B Thinking?

Qwen3 VL 235B A22B Thinking is the cheaper of the two: one 1,000-word request costs about 1,660 toman, about 1.3× cheaper than Qwen3.7 Max.

Which one has the larger context window?

Qwen3.7 Max, with 1,000,000 tokens.

Qwen3.7 Max vs Qwen3 VL 235B A22B Thinking

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. On cost, Qwen3 VL 235B A22B Thinking comes out about 1.3× cheaper.

Feature	Qwen3.7 Max	Qwen3 VL 235B A22B Thinking
Provider	Qwen (Alibaba)	Qwen (Alibaba)
Model id	qwen/qwen3.7-max	qwen/qwen3-vl-235b-a22b-thinking
Context	1,000,000 tokens	131,072 tokens
Max output	131,072 tokens	32,768 tokens
Input / 1M tokens	427,934 toman	116,050 toman
Output / 1M tokens	1,283,803 toman	1,160,500 toman
≈ one 1,000-word request	2,225 toman	1,660 toman
Input caching	85,587 toman / 1M	No
Image input	No	Yes
File input	No	No
Tool calling	Yes	Yes
JSON output	Yes	Yes
Reasoning mode	Yes	Yes

Which one for what?

Qwen3.7 Max

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

2,225 toman per 1,000 words · Model page

Qwen3 VL 235B A22B Thinking

Multi-step problems, maths, and tracking down a bug
Reading screenshots, invoices, and scanned forms
Agents that call your own APIs and database

1,660 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/qwen3.7-max",
    "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/qwen3.7-max",
    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/qwen3.7-max",
  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/qwen3.7-max',
    '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/qwen3.7-max",
		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-thinking"

More comparisons: all pairs · model rankings · full catalogue

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