Question 1

When is the exact release date of DeepSeek V4?

Accepted Answer

Expected March 2026, likely around Mar 2-8 (Next Week). See our release date analysis for more details.

Question 2

Is DeepSeek V4 actually open source?

Accepted Answer

Yes, rumors indicate an Apache 2.0 license with full open weights, continuing DeepSeek's open-source tradition. Read about the leaked GitHub repository.

Question 3

What is the leaked "MODEL1" codename?

Accepted Answer

"MODEL1" is the internal codename found in GitHub leaks, believed to be the specialized coding version of DeepSeek V4.

Question 4

How much will DeepSeek V4 API cost?

Accepted Answer

Estimates suggest ~$0.10-$0.14 per million tokens, making it ~97% cheaper than GPT-5. Check our API pricing guide.

Question 5

How to join the DeepSeek V4 waitlist?

Accepted Answer

Sign up via the official DeepSeek website or our notification form to get early access alerts.

Question 6

What is DeepSeek V4's parameter count?

Accepted Answer

It utilizes a massive 1 Trillion parameter MoE (Mixture of Experts) architecture, but with only ~32-40B active parameters per token for high efficiency.

Question 7

What is "Engram Memory" in V4?

Accepted Answer

A revolutionary conditional memory mechanism that allows for an effectively infinite context window by retrieving memories in O(1) time. Learn more about Engram Memory.

Question 8

What is mHC (Manifold-Constrained Hyper-Connections)?

Accepted Answer

An architectural innovation that stabilizes training for trillion-parameter models by geometrically constraining information flow. Read our deep dive on mHC Architecture.

Question 9

What is DeepSeek Sparse Attention (DSA)?

Accepted Answer

A technique that reduces computational costs by ~50% while supporting context windows exceeding 1 million tokens.

Question 10

Does DeepSeek V4 have "System 2" reasoning?

Accepted Answer

Yes, it reportedly features a "pause and think" mechanism (Chain of Thought) similar to OpenAI's o1, allowing it to plan before answering.

Question 11

DeepSeek V4 vs. GPT-5: Which is better?

Accepted Answer

While GPT-5 is a powerful dense model, DeepSeek V4 offers comparable reasoning at 1/10th the cost and includes open-weights flexibility. See the full V4 vs GPT-5 comparison.

Question 12

Is DeepSeek V4 better at coding than Claude 4.5?

Accepted Answer

Leaked benchmarks show V4 scoring 96.5% on HumanEval, potentially surpassing both Claude 4.5 and GPT-5 in specific coding tasks. View the leaked benchmarks.

Question 13

Can DeepSeek V4 fix bugs across an entire repository?

Accepted Answer

Yes, its massive context window and reasoning capabilities allow it to analyze full codebases for repo-level bug fixing.

Question 14

DeepSeek V4 vs V3: What's the upgrade?

Accepted Answer

V4 adds native multimodality, Engram Memory (infinite context), and a 40% jump in reasoning benchmarks over V3.

Question 15

Does it support image input/output?

Accepted Answer

V4 is natively multimodal, trained on code, text, and images simultaneously, capable of understanding UI screenshots and estimating code.

Question 16

Can I run DeepSeek V4 locally?

Accepted Answer

Yes, quantized versions (4-bit/8-bit) are designed to run on high-end consumer hardware like dual NVIDIA RTX 4090s. Read our local deployment guide.

Question 17

What are the hardware requirements for local inference?

Accepted Answer

67B version needs ~24GB VRAM. The full 1T MoE model requires enterprise-grade clusters or significant quantization.

Question 18

Does it run on Apple Silicon (Mac M3/M4)?

Accepted Answer

Optimized GGUF versions are expected to support Mac Studio/Pro with high unified memory (64GB+).

Question 19

What is the context window size?

Accepted Answer

Standard is 128k, but Engram versions support 1M+ to effectively infinite tokens.

Question 20

Is there a rate limit for the free version?

Accepted Answer

The web chat is expected to have a generous free tier (approx. 50 msg/hour), with paid tiers for higher limits.

Question 21

Does it support Python and Rust?

Accepted Answer

It is SOTA (State of the Art) for Python, Rust, C++, and JavaScript, trained on a massive specialized code corpus. See our coding guide.

Question 22

Can I use it with VS Code or Cursor?

Accepted Answer

Yes, it is fully compatible with Cursor, Continue.dev, and other AI coding assistants via API key.

Question 23

Is user data used for training?

Accepted Answer

API data is NOT trained on by default. Web chat data may be used unless opted out.

Question 24

Does it have Chinese language optimization?

Accepted Answer

DeepSeek V4 has industry-leading Chinese language understanding and generation, outperforming western models.

Question 25

Is there an official Mobile App?

Accepted Answer

Yes, an official app for iOS and Android is expected to launch alongside the model.

Feature	DeepSeek V3	DeepSeek V4	GPT-5.2	Claude 4.5	Gemini 3 Pro
Context Window	128k	Infinite	2M	1M	10M
Architecture	MoE	MHC (Multi-Head Contextual)	MoE	Dense	MoE
Memory Mechanism	KV Cache	Engram	KV Cache	KV Cache	KV Cache
Release Date	Jan 2024	Feb 2026	Late 2025	Mid 2025	Late 2025

Feature	DeepSeek V3	DeepSeek V4	GPT-5.2	Claude 4.5	Gemini 3 Pro
Context Window	128k	Infinite	2M	1M	10M
Architecture	MoE	MHC (Multi-Head Contextual)	MoE	Dense	MoE
Memory Mechanism	KV Cache	Engram	KV Cache	KV Cache	KV Cache
Release Date	Jan 2024	Feb 2026	Late 2025	Mid 2025	Late 2025

DeepSeek V4: The Engram-Powered Coding Monster Arrives Mar 2026

DeepSeek v4 Features

Super Coding Ability

Engram Architecture

Extreme Performance

Open Source Commitment

Ultra Low Cost

Chinese Optimization

Technical Specifications

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