Which is cheaper, Mistral Small 3.1 24B or Saba?

Saba is the cheaper of the two: one 1,000-word request costs about 302 toman.

Which one has the larger context window?

Mistral Small 3.1 24B, with 128,000 tokens.

Mistral Small 3.1 24B vs Saba

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	Mistral Small 3.1 24B	Saba
Provider	Mistral	Mistral
Model id	mistralai/mistral-small-3.1-24b-instruct	mistralai/mistral-saba
Context	128,000 tokens	32,768 tokens
Max output	102,400 tokens	26,214 tokens
Input / 1M tokens	101,834 toman	58,025 toman
Output / 1M tokens	161,019 toman	174,075 toman
≈ one 1,000-word request	342 toman	302 toman
Input caching	No	5,803 toman / 1M
Image input	Yes	No
File input	No	Yes
Tool calling	No	Yes
JSON output	No	Yes
Reasoning mode	No	No

Which one for what?

Mistral Small 3.1 24B

Reading screenshots, invoices, and scanned forms
High-volume work where cost per call decides

342 toman per 1,000 words · Model page

Saba

Agents that call your own APIs and database
High-volume work where cost per call decides

302 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": "mistralai/mistral-small-3.1-24b-instruct",
    "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="mistralai/mistral-small-3.1-24b-instruct",
    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: "mistralai/mistral-small-3.1-24b-instruct",
  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' => 'mistralai/mistral-small-3.1-24b-instruct',
    '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:    "mistralai/mistral-small-3.1-24b-instruct",
		Messages: []openai.ChatCompletionMessageParamUnion{openai.UserMessage("Introduce yourself in one sentence.")},
	})
	if err != nil {
		panic(err)
	}
	fmt.Println(resp.Choices[0].Message.Content)
}

model = "mistralai/mistral-saba"

More comparisons: all pairs · model rankings · full catalogue

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