DeepSeek R1 Online

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DeepSeek R1 Online is an open-source AI model for advanced reasoning that beats OpenAI o1. It offers free, no-login access and can run locally in your browser with WebGPU acceleration.

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At a glance

Pricing

Free · Open Source · Usage-based

Free tier

Yes

API

Yes

Skill level

Technical

About

What is DeepSeek R1 Online?

DeepSeek R1 Online is a revolutionary open-source AI model designed for advanced reasoning, mathematics, and coding tasks. It offers free, no-login access and boasts capabilities comparable to leading proprietary solutions like OpenAI o1, often at a significantly lower cost. Built on a sophisticated Mixture of Experts (MoE) architecture with 37B active/671B total parameters and 128K context length, DeepSeek R1 implements advanced reinforcement learning for self-verification and multi-step reflection. It achieves state-of-the-art performance on benchmarks like MATH-500 (97.3% accuracy) and Codeforces (96.3% percentile). The tool also supports local deployment via WebGPU and offers various distilled models for resource-constrained environments.

Best used for

Ideal for developers and data scientists who need to perform advanced mathematical reasoning, generate production-grade code, and solve complex problems. Especially valuable for those seeking a powerful, open-source AI model that can be deployed locally or accessed via a cost-effective API.

Common actions

perform advanced reasoning

generate code

solve complex math

understand natural language

deploy AI models

Capabilities

Key features

Advanced reasoning capabilities
Open-source MIT license
WebGPU local inference
MoE architecture
128K context length
Self-verification
Multi-step reflection

Target Audience

developerdata scientiststartup founderstudent

Integrations

Not yet documented

Pricing & Plans

Free · Open Source · Usage-based

Free

FAQs

What makes DeepSeek R1's architecture unique?

DeepSeek R1 utilizes a Mixture of Experts (MoE) system with 37B active/671B total parameters and 128K context support. It's optimized through pure reinforcement learning, setting new benchmarks in AI reasoning capabilities without supervised fine-tuning.

How does DeepSeek R1 compare to OpenAI o1 in pricing?

DeepSeek R1 is significantly more affordable, costing 90-95% less than OpenAI o1. For example, input tokens are $0.14/million (cache hit) compared to OpenAI o1's $15/million, offering substantial cost savings.

Can DeepSeek R1 be deployed locally?

Yes, DeepSeek R1 supports local deployment via WebGPU acceleration, vLLM/SGLang, and offers 6 distilled models ranging from 1.5B to 70B parameters for resource-constrained environments. This allows for in-browser inference without data being sent to a server.

Is DeepSeek R1 open source?

Yes, DeepSeek R1 is MIT-licensed, with full model weights available on GitHub. This allows for free use, modification, and commercialization, fostering open-source community collaboration and development.

What benchmarks demonstrate DeepSeek R1's performance?

DeepSeek R1 achieves state-of-the-art results, including 97.3% accuracy on MATH-500, a 96.3% percentile ranking on Codeforces, and a 79.8% pass rate on AIME 2024, positioning it among top-performing AI models globally.

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