Which is cheaper, DeepSeek V4 Flash Latest or Command R7B (12-2024)?

Command R7B (12-2024) is the cheaper of the two: one 1,000-word request costs about 71 toman.

Which one has the larger context window?

DeepSeek V4 Flash Latest, with 1,310,720 tokens.

DeepSeek V4 Flash Latest vs Command R7B (12-2024)

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	DeepSeek V4 Flash Latest	Command R7B (12-2024)
Provider	DeepSeek	Cohere
Model id	~deepseek/deepseek-v4-flash-latest	cohere/command-r7b-12-2024
Context	1,310,720 tokens	128,000 tokens
Max output	393,216 tokens	4,000 tokens
Input / 1M tokens	14,506 toman	10,880 toman
Output / 1M tokens	46,420 toman	43,519 toman
≈ one 1,000-word request	79 toman	71 toman
Input caching	3,772 toman / 1M	No
Image input	No	No
File input	No	No
Tool calling	Yes	No
JSON output	Yes	Yes
Reasoning mode	Yes	No

Which one for what?

DeepSeek V4 Flash Latest

Multi-step problems, maths, and tracking down a bug
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

79 toman per 1,000 words · Model page

Command R7B (12-2024)

High-volume work where cost per call decides

71 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": "~deepseek/deepseek-v4-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="~deepseek/deepseek-v4-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: "~deepseek/deepseek-v4-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' => '~deepseek/deepseek-v4-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:    "~deepseek/deepseek-v4-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 = "cohere/command-r7b-12-2024"

More comparisons: all pairs · model rankings · full catalogue

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