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Gemini 2.5 Flash vs DeepSeek V3

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, DeepSeek V3 comes out about 2.2× cheaper.

FeatureGemini 2.5 FlashDeepSeek V3
ProviderGoogleDeepSeek
Model idgoogle/gemini-2.5-flashdeepseek/deepseek-chat
Context1,048,576 tokens163,840 tokens
Max output65,535 tokens16,000 tokens
Input / 1M tokens103,866 toman89,117 toman
Output / 1M tokens865,548 toman356,156 toman
≈ one 1,000-word request1,260 toman579 toman
Input caching10,387 toman / 1MNo
Image inputYesNo
File inputYesNo
Tool callingYesYes
JSON outputYesYes
Reasoning modeYesNo

Which one for what?

Gemini 2.5 Flash

  • 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
1,260 toman per 1,000 words · Model page

DeepSeek V3

  • Agents that call your own APIs and database
579 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": "google/gemini-2.5-flash",
    "messages": [{"role": "user", "content": "Introduce yourself."}],
    "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="google/gemini-2.5-flash",
    messages=[{"role": "user", "content": "Introduce yourself."}],
    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: "google/gemini-2.5-flash",
  messages: [{ role: "user", content: "Introduce yourself." }],
  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' => 'google/gemini-2.5-flash',
    'messages' => [['role' => 'user', 'content' => 'Introduce yourself.']],
]);
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:    "google/gemini-2.5-flash",
		Messages: []openai.ChatCompletionMessageParamUnion{openai.UserMessage("Introduce yourself.")},
	})
	if err != nil {
		panic(err)
	}
	fmt.Println(resp.Choices[0].Message.Content)
}

model = "deepseek/deepseek-chat"

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Frequently asked

Which is cheaper, Gemini 2.5 Flash or DeepSeek V3?
DeepSeek V3 is the cheaper of the two: one 1,000-word request costs about 579 toman, about 2.2× cheaper than Gemini 2.5 Flash.
Which one has the larger context window?
Gemini 2.5 Flash, with 1,048,576 tokens.
Can I use Gemini 2.5 Flash and DeepSeek V3 with one API key?
Yes. An uttapen key reaches every model unless you gave it an allowed-models list, and each request is charged in toman to the same wallet; only the model value changes.

More comparisons: all pairs · model rankings · full catalogue

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