New DeepSeek V3-0324 Model Challenges GPT-4o and Claude-3.5

DeepSeek AI has announced a major upgrade to its flagship model — DeepSeek V3-0324. The model, available on GitHub and Hugging Face, not only catches up with but also surpasses closed alternatives like GPT-4o and Claude-3.5-Sonnet in several key areas.

At the core of the update is an enhanced Mixture-of-Experts (MoE) architecture, where 671 billion parameters are dynamically activated in chunks of 37 billion per token. The Multi-head Latent Attention technology reduces memory consumption by 60%, while Multi-Token Prediction boosts text generation speed by 1.8 times. The model has been trained on a dataset including math problems, code in 15 languages, and scientific papers. Training took 2.788 million GPU hours on H800 clusters — the equivalent of 318 years of continuous work on a single accelerator. The result: 89.3% accuracy in solving school-level math problems (GSM8K) and a 65.2% success rate in code generation (HumanEval) — 10–15% higher than previous open-source solutions.

The update has brought some unexpected improvements:

While the official update notes have not yet been released, the model’s size is reportedly 700 GB. It’s available via API with a unique "temperature calibration" system: the standard parameter of 1.0 is automatically adjusted to an optimal 0.3. For local deployment, developers are offered modified prompt templates with support for web search and file analysis — a feature previously available only in premium commercial solutions.

Experts predict that DeepSeek V3-0324 could disrupt the AI assistant market for programming and data analysis. Its open-source availability under an MIT license opens the door for customization — from business process automation to the creation of specialized scientific assistants.