Which is cheaper, Qwen3 Coder Plus or Qwen3.8 27B?

Qwen3.8 27B is the cheaper of the two: one 1,000-word request costs about 1,290 toman.

Which one has the larger context window?

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

Qwen3 Coder Plus vs Qwen3.8 27B

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 Coder Plus	Qwen3.8 27B
Provider	Qwen (Alibaba)	Qwen (Alibaba)
Model id	qwen/qwen3-coder-plus	qwen/qwen3.8-27b
Context	1,000,000 tokens	1,000,000 tokens
Max output	65,536 tokens	131,072 tokens
Input / 1M tokens	188,581 toman	121,853 toman
Output / 1M tokens	942,906 toman	870,375 toman
≈ one 1,000-word request	1,471 toman	1,290 toman
Input caching	37,716 toman / 1M	24,661 toman / 1M
Image input	No	Yes
File input	No	No
Tool calling	Yes	Yes
JSON output	Yes	Yes
Reasoning mode	No	Yes

Which one for what?

Qwen3 Coder Plus

Whole documents or a codebase in a single request
Agents that call your own APIs and database

1,471 toman per 1,000 words · Model page

Qwen3.8 27B

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

1,290 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-coder-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-coder-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-coder-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-coder-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-coder-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/qwen3.8-27b"

More comparisons: all pairs · model rankings · full catalogue

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