DeepSeek-R1-0528

DeepSeek-R1-0528 is a significant update to the original DeepSeek-R1 model, released on May 28, 2025, as a "minor trial update." However, the new version demonstrates such substantial improvements in reasoning quality that it outperforms the base version by more than 10 percentage points across nearly all benchmarks and confidently competes with current leading proprietary solutions. For example, on the AIME 2025 test, accuracy increased from 70% in the previous version to 87.5% in the current one. This achievement was made possible by enhanced depth of thinking during the reasoning process: whereas the earlier model used an average of 12K tokens per question, the new version averages 23K tokens per question.

A key distinction of DeepSeek-R1-0528 from its predecessor is the significant improvement in Chain-of-Thought (CoT) behavior, which has become more structured and deeper. The model is now capable of prolonged information processing. In addition to enhanced reasoning and logical inference capabilities, this version also offers a reduced hallucination rate, improved function calling support, and a better web development experience.

DeepSeek-R1-0528 represents a major step forward in the development of open reasoning models. The combination of improved reasoning capabilities, high performance in programming tasks, and availability under an open license makes this model an uncompromising choice as an engine for research and commercial projects where truly complex AI-driven problem-solving is required.

Announce Date: 28.05.2025
Parameters: 685B
Experts: 256
Activated at inference: 37B
Context: 164K
Layers: 61
Attention Type: Multi-head Latent Attention
Developer: DeepSeek
Transformers Version: 4.46.3
License: MIT

Use our pre-built public endpoints for free to test inference and explore DeepSeek-R1-0528 capabilities. You can obtain an API access token on the token management page after registration and verification.

An endpoint is a server with pre-installed software that automatically downloads neural network weights and launches an OpenAI-compatible API to handle incoming requests.

A private endpoint is created within the user's project, belongs exclusively to the user, and is billed per server configuration in accordance with the infrastructure pricing.

We recommend creating private endpoints when you need to:

• achieve maximum endpoint performance,
• access the full context window for processing large requests and conversations,
• ensure maximum security by processing data in a dedicated, isolated environment.

Contact our dedicated neural networks support team at support@immers.cloud or send your request to the sales department at sale@immers.cloud.