Compare DeepSeek and Grok AI models in 2025. Explore specs, performance, cost, and features to see which suits you best. Read now!

Key Points

Introduction

In the fast-evolving world of artificial intelligence, DeepSeek and Grok stand out as two prominent large language models (LLMs) with distinct approaches. This comparison will break down their origins, technical specs, performance, cost, accessibility, features, and future plans, helping you understand which might suit your needs better.

Origins and Background

DeepSeek, founded in July 2023 by Liang Wenfen in China, focuses on open-source models like DeepSeek-V3 and DeepSeek-R1, gaining attention for their efficiency and low cost. Conversely, Grok comes from xAI, Elon Musk’s company, and is integrated with X, with iterations leading to Grok 3, emphasizing curiosity and truth-seeking.

Model Specifications and Performance

DeepSeek-V3 boasts 671 billion parameters, with 37 billion active per token, trained on 14.8 trillion tokens, making it a Mixture-of-Experts (MoE) model. Grok 3’s parameter count isn’t public, but it’s trained on 12.8 trillion tokens using a supercomputer with 200,000 GPUs, also an MoE model. Performance varies; DeepSeek-V3 competes in benchmarks like MMLU, while Grok 3 claims superiority in math and science, though user tests show mixed results, with each excelling in different tasks.

Cost and Accessibility

DeepSeek’s open-source nature means it’s free to use, modify, and distribute, ideal for researchers and developers. Grok, however, requires a subscription, like X Premium+ at $40/month, limiting access to paying users, though it’s free until server capacity is reached.

Features and Future Plans

DeepSeek offers a range of models for various tasks, community-driven due to openness. Grok 3 introduces DeepSearch for reasoning and “Big Brain” mode for complex queries, integrated with X. Both aim to innovate, with DeepSeek potentially expanding into multimodal capabilities and xAI leveraging resources for enhanced reasoning.


Survey Note: Comprehensive Comparison of DeepSeek and Grok

In the rapidly evolving landscape of artificial intelligence, two notable players have emerged: DeepSeek and Grok. Both are large language models (LLMs) that promise to redefine how we interact with AI. This detailed comparison explores their origins, model specifications, performance, cost, accessibility, features, and future plans, providing a thorough analysis for readers to understand their differences and similarities.

Origin and Background

DeepSeek:

Grok:

Model Specifications

DeepSeek-V3:

Grok 3:

Performance

Both models have been evaluated on various benchmarks, with results varying by task:

A table summarizing benchmark performances, where available, is as follows:

BenchmarkDeepSeek-V3 ScoreGrok 3 Score
MMLUCompetitive79.9% (reported)
AIMENot specified93.3% (reported)
GPQANot specified84.6% (reported)
HumanEvalStrong (coding)Not specified

Note: Some scores are from official claims and may require independent verification.

Cost and Accessibility

Features

Future Plans

This comprehensive comparison highlights that DeepSeek and Grok cater to different user bases and needs, with DeepSeek’s open-source model appealing to cost-conscious developers and Grok’s subscription-based access offering advanced features for paying users. The choice ultimately depends on specific requirements, budget, and preferences regarding model transparency and accessibility.

Key Citations

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