Llama 3.1 Euryale 70B v2.2 vs GLM 4.5 Air
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, GLM 4.5 Air comes out about 1.7× cheaper.
| Feature | Llama 3.1 Euryale 70B v2.2 | GLM 4.5 Air |
|---|---|---|
| Provider | Sao10k | Z.ai (GLM) |
| Model id | sao10k/l3.1-euryale-70b | z-ai/glm-4.5-air |
| Context | 131,072 tokens | 131,072 tokens |
| Max output | 16,384 tokens | 98,304 tokens |
| Input / 1M tokens | 246,606 toman | 37,716 toman |
| Output / 1M tokens | 246,606 toman | 246,606 toman |
| ≈ one 1,000-word request | 641 toman | 370 toman |
| Input caching | No | 7,253 toman / 1M |
| Image input | No | No |
| File input | No | No |
| Tool calling | Yes | Yes |
| JSON output | Yes | No |
| Reasoning mode | No | Yes |
Which one for what?
Llama 3.1 Euryale 70B v2.2
- Agents that call your own APIs and database
641 toman per 1,000 words · Model page
GLM 4.5 Air
- Multi-step problems, maths, and tracking down a bug
- Agents that call your own APIs and database
- High-volume work where cost per call decides
370 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": "sao10k/l3.1-euryale-70b",
"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="sao10k/l3.1-euryale-70b",
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: "sao10k/l3.1-euryale-70b",
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' => 'sao10k/l3.1-euryale-70b',
'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: "sao10k/l3.1-euryale-70b",
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-4.5-air"
More comparisons: all pairs · model rankings · full catalogue
base_url = https://api.uttapen.ir/v1