Overview

DeepSeek V3.1 671B stands as a premier thinking model within the DeepSeek family, engineered for complex reasoning and extensive context handling. With 671 billion parameters, this architecture delivers exceptional performance on tasks requiring deep logical analysis, code generation, and multi-step problem solving. The massive 128,000-token context window enables developers to process entire codebases or lengthy documentation in a single pass, ensuring coherence across large-scale projects. Operating at FP16 precision, it balances high-fidelity output with efficient inference, making it a robust choice for demanding applications.

Available on LLM Resayil, this model is accessible starting at the starter tier, lowering the barrier to entry for enterprise-grade intelligence. While the 3.5x credit multiplier reflects its substantial computational requirements, the trade-off yields superior accuracy for critical workflows. The AGPL-3.0 license ensures transparency and flexibility for open-source initiatives, allowing developers to integrate powerful reasoning capabilities without restrictive proprietary constraints. For teams building advanced agents or analytical tools, DeepSeek V3.1 provides the necessary scale and precision to handle intricate dependencies effectively.

Specifications

Display Name DeepSeek V3.1 671B

Family DeepSeek

Category Thinking

Parameters 671B

Context Window 128,000 tokens

Quantization FP16

License AGPL-3.0

Min Tier Starter

Status Available

Pricing

3.5×

credits per token

1K 3,500 Credits

10K 35,000 Credits

100K 350,000 Credits

View Pricing Plans

Code Examples

from openai import OpenAI

client = OpenAI(
    base_url="https://llmapi.resayil.io/v1/",
    api_key="YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="deepseek-v3.1:671b",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

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

import anthropic

client = anthropic.Anthropic(
    base_url="https://llmapi.resayil.io/v1",
    api_key="YOUR_API_KEY"
)

message = client.messages.create(
    model="deepseek-v3.1:671b",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

print(message.content[0].text)

const response = await fetch(
    "https://llmapi.resayil.io/v1/chat/completions",
    {
        method: "POST",
        headers: {
            "Content-Type": "application/json",
            "Authorization": "Bearer YOUR_API_KEY"
        },
        body: JSON.stringify({
            model: "deepseek-v3.1:671b",
            messages: [
                { role: "user", content: "Hello!" }
            ]
        })
    }
);

const data = await response.json();
console.log(data.choices[0].message.content);

curl https://llmapi.resayil.io/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "deepseek-v3.1:671b",
    "messages": [
      {"role": "user", "content": "Hello!"}
    ]
  }'

Use Cases

Solving complex mathematical and logical reasoning problems

Processing entire codebases for refactoring and debugging

Summarizing lengthy legal documents for key insights

Generating detailed scientific research hypotheses and plans

Analyzing complex multi-step workflows for optimization strategies

In-Depth Guide

Full Guide

Complete Guide to DeepSeek V3.1 671B — LLM Resayil

DeepSeek V3.1 671B