Which is cheaper, Nova Pro 1.0 or Qwen3 Coder Plus?

Qwen3 Coder Plus is the cheaper of the two: one 1,000-word request costs about 1,471 toman.

Which one has the larger context window?

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

Nova Pro 1.0 vs Qwen3 Coder Plus

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	Nova Pro 1.0	Qwen3 Coder Plus
Provider	Amazon	Qwen (Alibaba)
Model id	amazon/nova-pro-v1	qwen/qwen3-coder-plus
Context	300,000 tokens	1,000,000 tokens
Max output	5,120 tokens	65,536 tokens
Input / 1M tokens	232,100 toman	188,581 toman
Output / 1M tokens	928,400 toman	942,906 toman
≈ one 1,000-word request	1,509 toman	1,471 toman
Input caching	No	37,716 toman / 1M
Image input	Yes	No
File input	No	No
Tool calling	Yes	Yes
JSON output	No	Yes
Reasoning mode	No	No

Which one for what?

Nova Pro 1.0

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

1,509 toman per 1,000 words · Model page

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

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": "amazon/nova-pro-v1",
    "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="amazon/nova-pro-v1",
    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: "amazon/nova-pro-v1",
  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' => 'amazon/nova-pro-v1',
    '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:    "amazon/nova-pro-v1",
		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-coder-plus"

More comparisons: all pairs · model rankings · full catalogue

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