Which is cheaper, GLM Flash Latest or Nova Lite 1.0?

Nova Lite 1.0 is the cheaper of the two: one 1,000-word request costs about 113 toman.

Which one has the larger context window?

GLM Flash Latest, with 1,310,720 tokens.

GLM Flash Latest vs Nova Lite 1.0

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 Flash Latest	Nova Lite 1.0
Provider	Z.ai (GLM)	Amazon
Model id	~z-ai/glm-flash-latest	amazon/nova-lite-v1
Context	1,310,720 tokens	300,000 tokens
Max output	131,072 tokens	5,120 tokens
Input / 1M tokens	20,671 toman	17,408 toman
Output / 1M tokens	68,905 toman	69,630 toman
≈ one 1,000-word request	116 toman	113 toman
Input caching	4,134 toman / 1M	No
Image input	Yes	Yes
File input	No	No
Tool calling	Yes	Yes
JSON output	Yes	No
Reasoning mode	Yes	No

Which one for what?

GLM Flash Latest

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

116 toman per 1,000 words · Model page

Nova Lite 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
High-volume work where cost per call decides

113 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-flash-latest",
    "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-flash-latest",
    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-flash-latest",
  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-flash-latest',
    '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-flash-latest",
		Messages: []openai.ChatCompletionMessageParamUnion{openai.UserMessage("Introduce yourself in one sentence.")},
	})
	if err != nil {
		panic(err)
	}
	fmt.Println(resp.Choices[0].Message.Content)
}

model = "amazon/nova-lite-v1"

More comparisons: all pairs · model rankings · full catalogue

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