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DEEPSEEK

DeepSeek is an AI company and a family of large language models based in Hangzhou, China. It was founded in 2023 and funded by High-Flyer, a well - known quantitative asset management giant. DeepSeek is dedicated to developing advanced large language models and related technologies. It has released several models, including DeepSeek LLM, DeepSeek Coder, DeepSeekMath, and DeepSeek - VL. The latest version, DeepSeek - V3, which was launched in December 2024, has 67.1 billion parameters and was trained on a dataset of 14.8 trillion tokens. It uses FP8 training and open - sources the native FP8 weights. Benchmark tests show that it outperforms Llama 3.1 and Qwen 2.5 while matching GPT - 4O and Claude 3.5 Sonnet. In addition, DeepSeek - R1, which was officially released on January 20, 2025, performs on a par with OpenAI O1 in terms of mathematics, code, and natural language reasoning tasks. DeepSeek's models have a wide range of applications, such as chat and coding scenarios, multilingual automatic translation, image generation, and AI painting. With their high performance and low cost, DeepSeek's models have quickly gained popularity. For example, on February 2, 2025, the DeepSeek app climbed to the top of the download charts in 140 countries on the Apple App Store and also topped the Android Play Store in the United States

deepseek

Enhancing Subgraph Indexing: Reduce eth_calls for Better Performance

Discover how reducing eth_calls can significantly boost subgraph indexing performance, as shared by The Graph Protocol's new best practices series.

by Terrill Dicki
Nov 17, 2025

deepseek

Exploring Subgraph Studio: A Guide to Building and Deploying Subgraphs

Learn how to utilize Subgraph Studio for developing and deploying subgraphs on The Graph's decentralized network. This guide covers essential steps and tools required for efficient subgraph creation.

by Rebeca Moen
Nov 17, 2025

DEEPSEEK

Enhancing Subgraph Indexing: Reduce eth_calls for Better Performance

Exploring Subgraph Studio: A Guide to Building and Deploying Subgraphs

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