Which is cheaper, Qwen3.6 35B A3B or Qwen3 Coder Flash?

Qwen3.6 35B A3B is the cheaper of the two: one 1,000-word request costs about 377 toman, about 1.2× cheaper than Qwen3 Coder Flash.

Which one has the larger context window?

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

Qwen3.6 35B A3B vs Qwen3 Coder Flash

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, Qwen3.6 35B A3B comes out about 1.2× cheaper.

Feature	Qwen3.6 35B A3B	Qwen3 Coder Flash
Provider	Qwen (Alibaba)	Qwen (Alibaba)
Model id	qwen/qwen3.6-35b-a3b	qwen/qwen3-coder-flash
Context	262,144 tokens	1,000,000 tokens
Max output	235,929 tokens	65,536 tokens
Input / 1M tokens	29,013 toman	56,574 toman
Output / 1M tokens	261,113 toman	282,872 toman
≈ one 1,000-word request	377 toman	441 toman
Input caching	14,506 toman / 1M	11,315 toman / 1M
Image input	Yes	No
File input	No	No
Tool calling	Yes	Yes
JSON output	Yes	Yes
Reasoning mode	Yes	No

Which one for what?

Qwen3.6 35B A3B

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
High-volume work where cost per call decides

377 toman per 1,000 words · Model page

Qwen3 Coder Flash

Whole documents or a codebase in a single request
Agents that call your own APIs and database
High-volume work where cost per call decides

441 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/qwen3.6-35b-a3b",
    "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/qwen3.6-35b-a3b",
    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/qwen3.6-35b-a3b",
  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/qwen3.6-35b-a3b',
    '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/qwen3.6-35b-a3b",
		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-flash"

More comparisons: all pairs · model rankings · full catalogue

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