Which is cheaper, Kimi K2.6 or GPT-3.5 Turbo 16k?

Kimi K2.6 is the cheaper of the two: one 1,000-word request costs about 1,867 toman, about 1.4× cheaper than GPT-3.5 Turbo 16k.

Which one has the larger context window?

Kimi K2.6, with 262,144 tokens.

Kimi K2.6 vs GPT-3.5 Turbo 16k

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, Kimi K2.6 comes out about 1.4× cheaper.

Feature	Kimi K2.6	GPT-3.5 Turbo 16k
Provider	Moonshot (Kimi)	OpenAI
Model id	moonshotai/kimi-k2.6	openai/gpt-3.5-turbo-16k
Context	262,144 tokens	16,385 tokens
Max output	235,929 tokens	4,096 tokens
Input / 1M tokens	275,619 toman	870,375 toman
Output / 1M tokens	1,160,500 toman	1,160,500 toman
≈ one 1,000-word request	1,867 toman	2,640 toman
Input caching	46,420 toman / 1M	No
Image input	Yes	No
File input	No	No
Tool calling	Yes	Yes
JSON output	Yes	Yes
Reasoning mode	Yes	No

Which one for what?

Kimi K2.6

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

1,867 toman per 1,000 words · Model page

GPT-3.5 Turbo 16k

Agents that call your own APIs and database

2,640 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": "moonshotai/kimi-k2.6",
    "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="moonshotai/kimi-k2.6",
    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: "moonshotai/kimi-k2.6",
  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' => 'moonshotai/kimi-k2.6',
    '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:    "moonshotai/kimi-k2.6",
		Messages: []openai.ChatCompletionMessageParamUnion{openai.UserMessage("Introduce yourself in one sentence.")},
	})
	if err != nil {
		panic(err)
	}
	fmt.Println(resp.Choices[0].Message.Content)
}

model = "openai/gpt-3.5-turbo-16k"

More comparisons: all pairs · model rankings · full catalogue

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