LLMs

LLMs

DeepSeek-V3 API

DeepSeek-V3 is specifically optimized for sustained conversational interactions and context-aware natural language understanding.

1RPC.ai

Reasoning

Speed

$0.27

/

$1.10

Input/Output

128,000

Context Window

DeepSeek Chat

DeepSeek Chat is an AI chatbot based on DeepSeek-V3, specifically optimized for sustained conversational interactions and context-aware natural language understanding. It supports interactive dialogues, long-context conversation, dynamic question-answering, and conversational tasks requiring detailed context retention and understanding.

What it’s optimized for

DeepSeek Chat is purpose-built for:

  • Efficient high-performance reasoning across diverse domains including math, coding, and scientific analysis

  • Handling extremely long contexts with up to 128,000 tokens for deep document or dialogue comprehension

  • Cost-effective training and inference enabled by selective activation (MoE) and FP8 precision

  • Fast token generation through multi-token prediction to support real-time or large-scale applications

  • Advanced reasoning with integrated reflection and verification mechanisms for reliable outputs

Typical use cases

DeepSeek Chat is particularly suited for:

  • Large-scale document analysis, including legal, research, and technical corpora

  • Complex multi-step question answering and problem-solving workflows

  • AI-powered code generation, review, and debugging with extended context

  • Real-time conversational agents requiring rich, accurate reasoning

Key characteristics

DeepSeek Reasoner differentiates itself from general-purpose LLMs through its methodical approach to reasoning and structured task execution. Where a general LLM may provide a quick answer, DeepSeek Reasoner focuses on transparency and completeness. It avoids jumping to conclusions, instead tracing a path through the logic or computation to support its output.

It handles symbolic math fluently, supports formal reasoning formats, and is capable of generating intermediate results and justifications. This makes it especially useful in settings where correctness and auditability are important, such as academic work, logic-driven code, or technical documentation.

Model architecture

DeepSeek Chat is built on DeepSeek-V3, centered on a Mixture-of-Experts transformer model combining multiple 34-billion parameter subnetworks, orchestrated by a router that selectively activates the best-suited experts per token. This strategy achieves high computational efficiency and scalability.

The model enhances the classic attention mechanism with Multi-Head Latent Attention, enabling multiple passes over input tokens to better capture critical information. Integrated multi-token prediction speeds inference by generating output tokens in batches rather than one at a time. Training leveraged the cutting-edge FP8 precision format to reduce memory footprint and accelerate calculation without sacrificing accuracy.

Why choose 1RPC.ai for DeepSeek-V3

  • Every call is directly tied to the exact model and version used, ensuring traceability and trust in your outputs

  • Execution runs inside hardware-backed enclaves, so the relay can’t access or log your request

  • Connect to multiple AI providers through a single API

  • Avoid provider lock-in with simple, pay-per-prompt pricing

  • Privacy by design with our zero-tracking infrastructure that eliminates metadata leakage and protects your activity

Summary

DeepSeek Chat is a high-precision open-source model that offers high efficiency and advanced reasoning capabilities.

By intelligently blending Mixture-of-Experts with innovative multi-token and multi-head attention techniques, it delivers fast, accurate, and cost-effective AI outputs.

Ideal for enterprises, researchers, and developers seeking a powerful, scalable, and transparent AI platform with strong multimodal and reasoning prowess.

DeepSeek Chat

DeepSeek Chat is an AI chatbot based on DeepSeek-V3, specifically optimized for sustained conversational interactions and context-aware natural language understanding. It supports interactive dialogues, long-context conversation, dynamic question-answering, and conversational tasks requiring detailed context retention and understanding.

What it’s optimized for

DeepSeek Chat is purpose-built for:

  • Efficient high-performance reasoning across diverse domains including math, coding, and scientific analysis

  • Handling extremely long contexts with up to 128,000 tokens for deep document or dialogue comprehension

  • Cost-effective training and inference enabled by selective activation (MoE) and FP8 precision

  • Fast token generation through multi-token prediction to support real-time or large-scale applications

  • Advanced reasoning with integrated reflection and verification mechanisms for reliable outputs

Typical use cases

DeepSeek Chat is particularly suited for:

  • Large-scale document analysis, including legal, research, and technical corpora

  • Complex multi-step question answering and problem-solving workflows

  • AI-powered code generation, review, and debugging with extended context

  • Real-time conversational agents requiring rich, accurate reasoning

Key characteristics

DeepSeek Reasoner differentiates itself from general-purpose LLMs through its methodical approach to reasoning and structured task execution. Where a general LLM may provide a quick answer, DeepSeek Reasoner focuses on transparency and completeness. It avoids jumping to conclusions, instead tracing a path through the logic or computation to support its output.

It handles symbolic math fluently, supports formal reasoning formats, and is capable of generating intermediate results and justifications. This makes it especially useful in settings where correctness and auditability are important, such as academic work, logic-driven code, or technical documentation.

Model architecture

DeepSeek Chat is built on DeepSeek-V3, centered on a Mixture-of-Experts transformer model combining multiple 34-billion parameter subnetworks, orchestrated by a router that selectively activates the best-suited experts per token. This strategy achieves high computational efficiency and scalability.

The model enhances the classic attention mechanism with Multi-Head Latent Attention, enabling multiple passes over input tokens to better capture critical information. Integrated multi-token prediction speeds inference by generating output tokens in batches rather than one at a time. Training leveraged the cutting-edge FP8 precision format to reduce memory footprint and accelerate calculation without sacrificing accuracy.

Why choose 1RPC.ai for DeepSeek-V3

  • Every call is directly tied to the exact model and version used, ensuring traceability and trust in your outputs

  • Execution runs inside hardware-backed enclaves, so the relay can’t access or log your request

  • Connect to multiple AI providers through a single API

  • Avoid provider lock-in with simple, pay-per-prompt pricing

  • Privacy by design with our zero-tracking infrastructure that eliminates metadata leakage and protects your activity

Summary

DeepSeek Chat is a high-precision open-source model that offers high efficiency and advanced reasoning capabilities.

By intelligently blending Mixture-of-Experts with innovative multi-token and multi-head attention techniques, it delivers fast, accurate, and cost-effective AI outputs.

Ideal for enterprises, researchers, and developers seeking a powerful, scalable, and transparent AI platform with strong multimodal and reasoning prowess.

DeepSeek Chat

DeepSeek Chat is an AI chatbot based on DeepSeek-V3, specifically optimized for sustained conversational interactions and context-aware natural language understanding. It supports interactive dialogues, long-context conversation, dynamic question-answering, and conversational tasks requiring detailed context retention and understanding.

What it’s optimized for

DeepSeek Chat is purpose-built for:

  • Efficient high-performance reasoning across diverse domains including math, coding, and scientific analysis

  • Handling extremely long contexts with up to 128,000 tokens for deep document or dialogue comprehension

  • Cost-effective training and inference enabled by selective activation (MoE) and FP8 precision

  • Fast token generation through multi-token prediction to support real-time or large-scale applications

  • Advanced reasoning with integrated reflection and verification mechanisms for reliable outputs

Typical use cases

DeepSeek Chat is particularly suited for:

  • Large-scale document analysis, including legal, research, and technical corpora

  • Complex multi-step question answering and problem-solving workflows

  • AI-powered code generation, review, and debugging with extended context

  • Real-time conversational agents requiring rich, accurate reasoning

Key characteristics

DeepSeek Reasoner differentiates itself from general-purpose LLMs through its methodical approach to reasoning and structured task execution. Where a general LLM may provide a quick answer, DeepSeek Reasoner focuses on transparency and completeness. It avoids jumping to conclusions, instead tracing a path through the logic or computation to support its output.

It handles symbolic math fluently, supports formal reasoning formats, and is capable of generating intermediate results and justifications. This makes it especially useful in settings where correctness and auditability are important, such as academic work, logic-driven code, or technical documentation.

Model architecture

DeepSeek Chat is built on DeepSeek-V3, centered on a Mixture-of-Experts transformer model combining multiple 34-billion parameter subnetworks, orchestrated by a router that selectively activates the best-suited experts per token. This strategy achieves high computational efficiency and scalability.

The model enhances the classic attention mechanism with Multi-Head Latent Attention, enabling multiple passes over input tokens to better capture critical information. Integrated multi-token prediction speeds inference by generating output tokens in batches rather than one at a time. Training leveraged the cutting-edge FP8 precision format to reduce memory footprint and accelerate calculation without sacrificing accuracy.

Why choose 1RPC.ai for DeepSeek-V3

  • Every call is directly tied to the exact model and version used, ensuring traceability and trust in your outputs

  • Execution runs inside hardware-backed enclaves, so the relay can’t access or log your request

  • Connect to multiple AI providers through a single API

  • Avoid provider lock-in with simple, pay-per-prompt pricing

  • Privacy by design with our zero-tracking infrastructure that eliminates metadata leakage and protects your activity

Summary

DeepSeek Chat is a high-precision open-source model that offers high efficiency and advanced reasoning capabilities.

By intelligently blending Mixture-of-Experts with innovative multi-token and multi-head attention techniques, it delivers fast, accurate, and cost-effective AI outputs.

Ideal for enterprises, researchers, and developers seeking a powerful, scalable, and transparent AI platform with strong multimodal and reasoning prowess.

Like this article? Share it.

Implement

Implement

Get started with an API-friendly relay

Send your first request to verified LLMs with a single code snippet.

import requests
import json

response = requests.post(
    url="https://1rpc.ai/v1/chat/completions",
    headers={
        "Authorization": "Bearer <1RPC_AI_API_KEY>",
        "Content-type": "application/json",
    },
    data=json.dumps ({
        "model": "deepseek-chat",
        "messages": [
            {
                "role": "user",
                "content": "What is the meaning of life?"
            }
        ]
    })
)

Copy and go

Copied!

import requests
import json

response = requests.post(
    url="https://1rpc.ai/v1/chat/completions",
    headers={
        "Authorization": "Bearer <1RPC_AI_API_KEY>",
        "Content-type": "application/json",
    },
    data=json.dumps ({
        "model": "deepseek-chat",
        "messages": [
            {
                "role": "user",
                "content": "What is the meaning of life?"
            }
        ]
    })
)

Copy and go

Copied!

Pricing

Pricing

Estimate Usage Across Any AI Model

Adjust input and output size to estimate token usage and costs.

Token Calculator for DeepSeek-V3

Input (100)

100

Output (1000 )

1000

$0.0011

Total cost per million tokens

Learn about Pricing

Learn about Pricing