Which is cheaper, Uncensored or Codestral 2508?

Uncensored is the cheaper of the two: one 1,000-word request costs about 415 toman.

Which one has the larger context window?

Codestral 2508, with 256,000 tokens.

Uncensored vs Codestral 2508

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	Uncensored	Codestral 2508
Provider	Cognitive Computations	Mistral
Model id	cognitivecomputations/dolphin-mistral-24b-venice-edition	mistralai/codestral-2508
Context	128,000 tokens	256,000 tokens
Max output	8,192 tokens	204,800 tokens
Input / 1M tokens	58,025 toman	87,038 toman
Output / 1M tokens	261,113 toman	261,113 toman
≈ one 1,000-word request	415 toman	453 toman
Input caching	No	8,704 toman / 1M
Image input	No	No
File input	No	Yes
Tool calling	No	Yes
JSON output	Yes	Yes
Reasoning mode	No	No

Which one for what?

Uncensored

High-volume work where cost per call decides

415 toman per 1,000 words · Model page

Codestral 2508

Whole documents or a codebase in a single request
Agents that call your own APIs and database
High-volume work where cost per call decides

453 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": "cognitivecomputations/dolphin-mistral-24b-venice-edition",
    "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="cognitivecomputations/dolphin-mistral-24b-venice-edition",
    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: "cognitivecomputations/dolphin-mistral-24b-venice-edition",
  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' => 'cognitivecomputations/dolphin-mistral-24b-venice-edition',
    '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:    "cognitivecomputations/dolphin-mistral-24b-venice-edition",
		Messages: []openai.ChatCompletionMessageParamUnion{openai.UserMessage("Introduce yourself in one sentence.")},
	})
	if err != nil {
		panic(err)
	}
	fmt.Println(resp.Choices[0].Message.Content)
}

model = "mistralai/codestral-2508"

More comparisons: all pairs · model rankings · full catalogue

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