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DeepSeek-R1T2-Chimera

입력:$0.2416/M
출력:$0.2416/M
출시일:Oct 1, 2025

DeepSeek-AI의 R1-0528, R1, V3-0324를 병합해 만든 671B 파라미터 Mixture of Experts 텍스트 생성 모델로, 최대 60k tokens의 컨텍스트를 지원합니다.

상업적 사용

DeepSeek-R1T2-Chimera의 Playground

DeepSeek-R1T2-Chimera의 Playground를 탐색하세요 — 모델을 테스트하고 실시간으로 쿼리를 실행하는 대화형 환경입니다. 프롬프트를 시도하고, 매개변수를 조정하며, 즉시 반복하여 개발을 가속화하고 사용 사례를 검증하세요.

Technical Specifications of deepseek-r1t2-chimera

SpecificationDetails
Model IDdeepseek-r1t2-chimera
Model typeText generation
ArchitectureMixture of Experts (MoE)
Parameter count671B parameters
Context lengthUp to 60,000 tokens
Training / merge basisMerged from DeepSeek-AI's R1-0528, R1, and V3-0324
Primary modalityText
Best forLong-context reasoning, structured generation, summarization, analysis, and general-purpose text completion

What is deepseek-r1t2-chimera?

deepseek-r1t2-chimera is a large-scale 671B parameter Mixture of Experts text generation model available through CometAPI. It is built from a merged model lineage combining DeepSeek-AI's R1-0528, R1, and V3-0324, giving developers a single endpoint designed for advanced text generation and reasoning workloads.

With support for up to 60k tokens of context, deepseek-r1t2-chimera is suitable for applications that need to process long prompts, extended conversations, large documents, or multi-step instructions. It can be used for tasks such as content generation, analytical writing, summarization, classification through prompting, and other natural language workflows where broad context retention matters.

Main features of deepseek-r1t2-chimera

  • 671B MoE architecture: Delivers large-scale generative capability through a Mixture of Experts design aimed at handling complex language tasks efficiently.
  • 60k token context window: Supports long-form interactions and large prompt payloads, making it useful for document-heavy and multi-turn use cases.
  • Merged DeepSeek lineage: Combines elements from DeepSeek-AI's R1-0528, R1, and V3-0324 to provide a unified model endpoint.
  • General-purpose text generation: Suitable for drafting, rewriting, summarizing, extracting structured outputs, and instruction-following workflows.
  • Reasoning-oriented usage: Well suited for prompts that require multi-step analysis, synthesis, and detailed written responses.
  • CometAPI compatibility: Accessible through CometAPI using the stable platform model identifier deepseek-r1t2-chimera.

How to access and integrate deepseek-r1t2-chimera

Step 1: Sign Up for API Key

To get started, create a CometAPI account and generate your API key from the dashboard. Once you have your key, store it securely and use it to authenticate requests to the CometAPI endpoint.

Step 2: Send Requests to deepseek-r1t2-chimera API

After obtaining your API key, send chat completion requests to the CometAPI API using the model ID deepseek-r1t2-chimera.

curl --request POST \
  --url https://api.cometapi.com/v1/chat/completions \
  --header "Authorization: Bearer $COMETAPI_API_KEY" \
  --header "Content-Type: application/json" \
  --data '{
    "model": "deepseek-r1t2-chimera",
    "messages": [
      {
        "role": "user",
        "content": "Write a concise summary of the following article."
      }
    ]
  }'
from openai import OpenAI

client = OpenAI(
    api_key="YOUR_COMETAPI_API_KEY",
    base_url="https://api.cometapi.com/v1"
)

response = client.chat.completions.create(
    model="deepseek-r1t2-chimera",
    messages=[
        {"role": "user", "content": "Write a concise summary of the following article."}
    ]
)

print(response.choices[0].message.content)

Step 3: Retrieve and Verify Results

Once the API returns a response, parse the generated output from the response object and validate it according to your application's needs. For production workflows, you may also want to add retries, output checks, schema validation, and human review for sensitive or high-importance use cases.

DeepSeek-R1T2-Chimera 가격

[모델명]의 경쟁력 있는 가격을 살펴보세요. 다양한 예산과 사용 요구에 맞게 설계되었습니다. 유연한 요금제로 사용한 만큼만 지불하므로 요구사항이 증가함에 따라 쉽게 확장할 수 있습니다. [모델명]이 비용을 관리 가능한 수준으로 유지하면서 프로젝트를 어떻게 향상시킬 수 있는지 알아보세요.

Comet Price (USD / M Tokens)Official Price (USD / M Tokens)Discount
입력:$0.2416/M
출력:$0.2416/M
입력:$0.302/M
출력:$0.302/M
-20%

DeepSeek-R1T2-Chimera의 샘플 코드 및 API

[모델 이름]의 포괄적인 샘플 코드와 API 리소스에 액세스하여 통합 프로세스를 간소화하세요. 자세한 문서는 단계별 가이드를 제공하여 프로젝트에서 [모델 이름]의 모든 잠재력을 활용할 수 있도록 돕습니다.

#!/bin/bash
# Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here

curl https://api.cometapi.com/v1/chat/completions \
     --header "Authorization: Bearer $COMETAPI_KEY" \
     --header "content-type: application/json" \
     --data \
'{
    "model": "deepseek-r1t2-chimera",
    "messages": [
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Hello!"}
    ]
}'

cURL Code Example

#!/bin/bash
# Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here

curl https://api.cometapi.com/v1/chat/completions \
     --header "Authorization: Bearer $COMETAPI_KEY" \
     --header "content-type: application/json" \
     --data \
'{
    "model": "deepseek-r1t2-chimera",
    "messages": [
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Hello!"}
    ]
}'

Python Code Example

from openai import OpenAI
import os

# Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here
COMETAPI_KEY = os.environ.get("COMETAPI_KEY") or "<YOUR_COMETAPI_KEY>"
BASE_URL = "https://api.cometapi.com/v1"

client = OpenAI(base_url=BASE_URL, api_key=COMETAPI_KEY)

completion = client.chat.completions.create(
    model="deepseek-r1t2-chimera",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Hello!"},
    ],
)

print(completion.choices[0].message.content)

JavaScript Code Example

import OpenAI from "openai";

// Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here
const COMETAPI_KEY = process.env.COMETAPI_KEY || "<YOUR_COMETAPI_KEY>";
const BASE_URL = "https://api.cometapi.com/v1";

const client = new OpenAI({
  apiKey: COMETAPI_KEY,
  baseURL: BASE_URL,
});

async function main() {
  const completion = await client.chat.completions.create({
    model: "deepseek-r1t2-chimera",
    messages: [
      { role: "system", content: "You are a helpful assistant." },
      { role: "user", content: "Hello!" },
    ],
  });

  console.log(completion.choices[0].message.content);
}

main();