Which is cheaper, MiniMax M2.7 (free) or MiniMax M3 (free)?

MiniMax M2.7 (free) is the cheaper of the two: one 1,000-word request costs about 0 toman.

Which one has the larger context window?

MiniMax M3 (free), with 1,048,576 tokens.

MiniMax M2.7 (free) vs MiniMax M3 (free)

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	MiniMax M2.7 (free)	MiniMax M3 (free)
Provider	MiniMax	MiniMax
Model id	minimax/minimax-m2.7:free	minimax/minimax-m3:free
Context	196,608 tokens	1,048,576 tokens
Max output	176,947 tokens	943,718 tokens
Input / 1M tokens	0 toman	0 toman
Output / 1M tokens	0 toman	0 toman
≈ one 1,000-word request	0 toman	0 toman
Input caching	No	No
Image input	No	Yes
File input	No	No
Tool calling	Yes	Yes
JSON output	Yes	Yes
Reasoning mode	Yes	Yes

Which one for what?

MiniMax M2.7 (free)

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

0 toman per 1,000 words · Model page

MiniMax M3 (free)

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

0 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": "minimax/minimax-m2.7:free",
    "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="minimax/minimax-m2.7:free",
    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: "minimax/minimax-m2.7:free",
  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' => 'minimax/minimax-m2.7:free',
    '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:    "minimax/minimax-m2.7:free",
		Messages: []openai.ChatCompletionMessageParamUnion{openai.UserMessage("Introduce yourself in one sentence.")},
	})
	if err != nil {
		panic(err)
	}
	fmt.Println(resp.Choices[0].Message.Content)
}

model = "minimax/minimax-m3:free"

More comparisons: all pairs · model rankings · full catalogue

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