Which is cheaper, GLM 5.1 or GLM 5.2?

GLM 5.1 is the cheaper of the two: one 1,000-word request costs about 1,509 toman.

Which one has the larger context window?

GLM 5.2, with 1,048,576 tokens.

GLM 5.1 vs GLM 5.2

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	GLM 5.1	GLM 5.2
Provider	Z.ai (GLM)	Z.ai (GLM)
Model id	z-ai/glm-5.1	z-ai/glm-5.2
Context	204,800 tokens	1,048,576 tokens
Max output	128,000 tokens	131,072 tokens
Input / 1M tokens	280,261 toman	280,261 toman
Output / 1M tokens	880,820 toman	880,820 toman
≈ one 1,000-word request	1,509 toman	1,509 toman
Input caching	52,048 toman / 1M	56,052 toman / 1M
Image input	No	No
File input	No	No
Tool calling	Yes	Yes
JSON output	Yes	Yes
Reasoning mode	Yes	Yes

Which one for what?

GLM 5.1

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

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

GLM 5.2

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

1,509 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": "z-ai/glm-5.1",
    "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="z-ai/glm-5.1",
    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: "z-ai/glm-5.1",
  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' => 'z-ai/glm-5.1',
    '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:    "z-ai/glm-5.1",
		Messages: []openai.ChatCompletionMessageParamUnion{openai.UserMessage("Introduce yourself in one sentence.")},
	})
	if err != nil {
		panic(err)
	}
	fmt.Println(resp.Choices[0].Message.Content)
}

model = "z-ai/glm-5.2"

More comparisons: all pairs · model rankings · full catalogue

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