‘Deepseek V4 Coming Soon: Programming Capabilities May Surpass Claude and GPT,

Author's Note: Deepseek V4 is expected to launch in mid-February, focusing on programming capabilities. Internal testing suggests it may surpass Claude and GPT. You can now access the full version of Deepseek V3.2 at 20% off the official price through API-Yi.

On January 9, 2026, according to The Information, Deepseek V4 is planned for release in mid-February, with a focus on enhanced programming capabilities. Internal testing indicates that V4's performance on coding tasks may surpass Anthropic's Claude and OpenAI's GPT series.

Core Value: Stay updated on the latest Deepseek V4 developments and experience the powerful capabilities of the full V3.2 version at 20% off the official price through API-Yi.

Deepseek V4 Core Information Overview

Based on multiple reports, here's what is currently known about Deepseek V4:

Why Deepseek V4 is Worth Anticipating

Deepseek V4 is not a simple version iteration, but rather a flagship model specifically optimized for programming scenarios. Unlike the R1 which focuses on pure reasoning, V4 is a hybrid model supporting both reasoning and non-reasoning tasks, targeting the enterprise developer market.

Three Major Technical Highlights of Deepseek V4:

1. Breakthrough in Extended Code Prompt Processing

   • Based on V3.2-Exp's Sparse Attention technology
   • Supports processing complete codebases of complex software projects
   • Significant for full-stack developers and large project maintainers

2. Comprehensive Programming Capability Enhancement

   • Internal tests show coding tasks surpassing Claude and GPT
   • Aiming to challenge Claude Opus 4.5's 80.9% record on SWE-bench Verified
   • Covers all scenarios including code generation, debugging, and refactoring

3. Continued MoE Architecture Advantages

   • Inherits the Mixture of Experts architecture from V3 series
   • Higher efficiency than traditional dense models
   • Inference costs expected to be further reduced

Industry Observation: Deepseek's focus on the programming domain directly targets the most commercially valuable enterprise developer market. High-precision code generation capabilities can be directly converted into revenue, making this a precise strategic choice.

Deepseek V3.2 Full Version Now Available

While waiting for the V4 release, Deepseek V3.2 is already one of the most powerful open-source large language models available. Through the APIYi platform, you can use the V3.2 full version at 20% off the official website price.

Deepseek V3.2 Core Capabilities

Deepseek V3.2 Technical Specifications

• Total Parameters: 685B (685 billion)
• Active Parameters: 37B (MoE architecture activates only a portion of parameters each time)
• Context Length: 128,000 tokens
• Architecture: Transformer + DeepSeek Sparse Attention + MoE
• Open Source License: MIT License (fully open source)

Why Deepseek V3.2 is Both Affordable and Powerful

Deepseek's MoE (Mixture of Experts) architecture is the key. Although the total parameters reach 685B, only 37B parameters are activated during each inference, which means:

• Inference cost reduced by 50-75%
• Maintains performance levels close to GPT-5
• API pricing is only 1/10 of competitors

APIYi Deepseek V3.2 Usage Guide

By using Deepseek V3.2 through the APIYi platform, you can enjoy 20% off the official website price, while getting more stable service and a unified interface.

Deepseek V3.2 API Quick Start

import openai

client = openai.OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://vip.apiyi.com/v1"
)

response = client.chat.completions.create(
    model="deepseek-chat",  # Deepseek V3.2 full version
    messages=[
        {"role": "system", "content": "You are a professional programming assistant"},
        {"role": "user", "content": "Implement an efficient LRU cache in Python"}
    ],
    max_tokens=2000
)
print(response.choices[0].message.content)

import openai

client = openai.OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://vip.apiyi.com/v1"
)

def chat_with_deepseek(prompt: str, stream: bool = False):
    """
    Chat with Deepseek V3.2

    Args:
        prompt: User input
        stream: Whether to use streaming output
    """
    messages = [
        {"role": "system", "content": "You are a professional programming assistant, skilled in code generation, debugging, and optimization"},
        {"role": "user", "content": prompt}
    ]

    if stream:
        # Streaming output
        response = client.chat.completions.create(
            model="deepseek-chat",
            messages=messages,
            stream=True,
            max_tokens=4000
        )
        for chunk in response:
            if chunk.choices[0].delta.content:
                print(chunk.choices[0].delta.content, end="", flush=True)
        print()
    else:
        # Regular output
        response = client.chat.completions.create(
            model="deepseek-chat",
            messages=messages,
            max_tokens=4000
        )
        return response.choices[0].message.content

# Usage example
code = chat_with_deepseek("Implement a Promise concurrency controller in TypeScript that limits the number of Promises executing simultaneously")
print(code)

# Streaming output example
chat_with_deepseek("Explain what Python's GIL is and how to work around it", stream=True)

Deepseek V3.2 API Pricing Comparison

Cost Optimization: For budget-sensitive projects, Deepseek V3.2 is currently the most cost-effective choice. By calling through the APIYi apiyi.com platform, you not only enjoy a 20% discount, but also get more stable service and Chinese technical support.

Deepseek V4 Technical Predictions

Based on currently disclosed information and the technical evolution of the V3 series, we can make the following reasonable predictions about V4:

Possible Technical Features of Deepseek V4

1. Enhanced Sparse Attention Mechanism

V3.2-Exp has already implemented fine-grained sparse attention. V4 will likely further optimize this foundation to achieve:

• Longer effective context windows
• Lower long-context inference costs
• Better cross-file code understanding capabilities

2. New Training Methods

On December 31, 2025, Deepseek published the "Manifold-Constrained Hyper-Connections (mHC)" method, which improves training stability and has likely been applied to V4's training.

3. Specialized Code Training Data

Similar to the large-scale agent training data introduced in V3.2 (1800+ environments, 85000+ complex instructions), V4 may possess even larger-scale specialized code training data.

Deepseek V4's Target Competitors

Technical Observation: If V4 can truly surpass Claude Opus 4.5 on SWE-bench, it would mark the first time an open-source model tops the most authoritative code benchmark—a significant milestone.

Developer Response Strategies

Current Phase: Leverage Deepseek V3.2

With approximately one month until V4's release, developers should:

1. Familiarize with Deepseek API

   • Register an account through APIYI apiyi.com
   • Obtain free testing credits
   • Become familiar with API calling methods

2. Evaluate Business Scenario Compatibility

   • Test V3.2's performance on your code tasks
   • Compare effectiveness and costs with other models
   • Establish performance baselines for post-V4 comparison

3. Focus on Long Context Capabilities

   • V3.2 already supports 128K context
   • Try processing large codebases
   • Test cross-file code understanding capabilities

Post-V4 Release: Rapid Evaluation and Switching

# On the APIYI platform, switching models only requires modifying the model parameter
response = client.chat.completions.create(
    model="deepseek-v4",  # Switch after V4 release
    messages=[{"role": "user", "content": "..."}]
)

Platform Advantage: APIYI apiyi.com typically supports new models immediately upon release. Using a unified interface, switching models requires only changing one parameter, with no other code modifications needed.

FAQ

Summary

The transformative changes Deepseek V4 will bring:

1. Coding capability breakthrough: Internal testing suggests it may surpass Claude and GPT, aiming for the top of SWE-bench
2. Ultra-long code processing: Based on sparse attention technology, with significant advantages in complex project development
3. Mid-February release: Expected to launch around the Lunar New Year, allowing developers to prepare in advance

What you can do now:

Use the full version of Deepseek V3.2 through APIYI apiyi.com at 20% off the official website price, get familiar with the API interface early, establish performance benchmarks, and prepare for quick evaluation when V4 is released.

Author: Technical Team
Technical Discussion: Feel free to share your expectations for Deepseek V4 in the comments. For more AI development resources, visit APIYI apiyi.com

References:

• The Information – DeepSeek To Release Next Flagship AI Model: theinformation.com
• Decrypt – Insiders Say DeepSeek V4 Will Beat Claude and ChatGPT: decrypt.co
• Cybernews – DeepSeek to launch coding-focused AI: cybernews.com
• DeepSeek API Docs – V3.2 Release: api-docs.deepseek.com