deepseek-r1.com

What is deepseek-r1.com?

This is a third-party fan site that provides information on the DeepSeek-R1 model, offers demonstrations of external chat functions, and provides download options. The site makes it clear that it has no connection to DeepSeek; therefore, it should not be considered an official DeepSeek website, official application, or official API platform.

The website name and the title of the home page emphasize R1, but the two experience options available currently are different: the home page uses DeepSeek-VL2-small, while the WebGPU version runs the lightweight R1 distillation model. Users should judge the capabilities based on the actual name of the model, rather than relying solely on the page title.

Current feature status

What can you do in the chat on the home page?

The chat area on the current homepage is based on the external demonstration of DeepSeek-VL2-small; it can receive text and images, and it allows for adjustments to parameters such as top-p, temperature, repetition penalty, maximum generation length, and history length. It is suitable for low-risk visual question-answering tasks and for testing models, but it cannot be used to evaluate the reasoning capabilities of DeepSeek-R1.

• Text Q&A: Enter a question, description, or instruction to receive a textual response.
• Image understanding: Upload an image and ask about its content, objects, relationships, or visual details.
• Generation control: Adjust randomness, degree of repetition, and answer length to observe differences in the output.
• Session operations: Create a new conversation, stop generation, regenerate, or remove the previous round.
• External dependencies: Functions, queuing, model updates, and data processing are affected by embedded services.

WebGPU local inference

The WebGPU page runs the ONNX version of DeepSeek-R1-Distill-Qwen-1.5B; inference is carried out in the browser using Transformers.js and ONNX Runtime Web. The prompt can remain on the local device during the inference process, but the model file still needs to be downloaded the first time it is accessed. Accessing the page and making requests for resources still generates network metadata.

• Model size: 1.5B parameters in the distilled version, which is much smaller than the full DeepSeek-R1.
• Execution location: Browsers that support WebGPU, as well as local CPU, GPU, and memory resources.
• Internet connection requirement: An internet connection is needed to download the model and page resources for the first time; once caching is complete, it can be used offline under suitable conditions.
• Applicable tasks: short Q&A, basic reasoning, learning experiments, and text with low local privacy sensitivity.
• Performance limits: Speed, maximum context size, and stability are influenced by the browser, video memory, RAM, and the device’s cooling capabilities.

The difference between the two experiences

Usage tutorial

Use the chat on the home page.

1. Upon arriving on the home page, first check the model name displayed on the embedded interface to confirm that it is DeepSeek-VL2-small.
2. Enter only test content that does not contain personal information, account credentials, trade secrets, or customer data.
3. When image understanding is required, upload non-sensitive images for which you have usage rights, and remove any unnecessary EXIF data as well as identification information.
4. Adjust the length of the response and the sampling parameters according to the task, and then verify facts, calculations, and visual judgments.
5. If there are login, permission, or file request requests from the external interface, re-verify the recipient before deciding whether to proceed.

Demo using WebGPU

1. Use the latest version of a desktop browser that supports WebGPU, and close any other pages that may be using a large amount of video memory.
2. Open the WebGPU page and wait for the model file to be downloaded and initialized; the initial loading time depends on the network and the device.
3. Start with brief prompts to verify the generation speed, memory usage, and browser stability.
4. Gradually increase the complexity of the tasks to prevent the page from becoming unresponsive due to the entry of excessively long text at once.
5. For offline use, ensure that the model resources are cached before disconnecting from the internet to conduct tests; if the browser’s cache is cleared, the resources need to be downloaded again.

Suitable for users and scenarios

• Students who are new to open-source inference models and wish to understand the differences between R1 and distillation models.
• Users who need to test lightweight local inference in a browser and are not willing to set up a Python environment.
• Users with non-sensitive tasks who wish to experience the image understanding capabilities of DeepSeek-VL2-small.
• Researchers looking for the official repository of DeepSeek-R1, as well as access to the model weights and technical documentation.
• Developers and learners who need to verify the WebGPU inference performance of devices as well as their browser compatibility.

Tasks that are not suitable

• It is required to confirm that the response comes from a formal model evaluation using the full DeepSeek-R1.
• Upload identification documents, medical records, internal documents, customer data, unpublished code, or contracts.
• Production applications that require service level agreements, stable APIs, auditing capabilities, team permissions, or enterprise support.
• High-risk decisions that rely on accurate legal, medical, financial, security, or engineering conclusions.
• Extend the performance of the lightweight 1.5B distilled version to that of the full 671B model.

Free, prices, and refunds

The site currently does not offer any paid subscription plans, points, membership-related billing pages, or corporate quotes; external chat functions and WebGPU demonstrations are available for free. The free version does not mean unlimited use forever – the external hosting space may experience waiting times, traffic restrictions, suspensions, or changes in the models used.

The token price displayed on the home page is based on historical data from DeepSeek’s official API; it does not represent the pricing applied by this fan site, nor does it reflect the current official prices. The site lacks a verifiable purchasing process, and as a result, there is no clear refund policy in place.

Models and licenses

The official code and model weights of DeepSeek-R1 are licensed under the MIT License, which permits commercial use, modification, derivation, and distillation. This license applies to DeepSeek’s official model projects only; it is not valid for third-party websites, articles, trademarks, or embedded services.

API, SDK, and on-premises deployment

This platform does not offer its own APIs, SDKs, plugins, or developer consoles. Users who need official APIs should turn to DeepSeek’s official platform or other verified model providers, and verify separately the details related to the models, prices, data policies, and service terms.

Developers who need complete control over the environment can select weights from the official DeepSeek-R1 project and then deploy the model using compatible inference frameworks. The full model requires significant amounts of memory on multiple machines as well as advanced engineering skills; the 1.5B to 70B version of this model is more suitable for testing at different hardware levels.

Platforms and applications

Privacy and security

The site’s privacy page still contains a large amount of text from WordPress’ default templates; it only gives general information regarding comments, IP addresses, browser identifiers, cookies, Gravatar, account details, and embedded content. It does not provide a detailed explanation of how data is processed in relation to chat prompts, image uploads, external iframes, analysis scripts, and local model caching.

• The chat on the home page sends inputs and images to external hosting services for processing; it cannot be understood as a local processing mechanism using WebGPU.
• WebGPU inference can be carried out locally, but site visits, model downloads, and third-party resources still generate network requests.
• Comments and their metadata may be retained indefinitely, while registration details can be viewed and edited by administrators.
• Externally embedded content may use its own cookies, tracking mechanisms, and account status; it is necessary to review each of their respective policies.
• Do not submit passwords, identification information, customer data, internal documents, proprietary code, or unpublished research.
• The site does not offer any guarantees regarding enterprise security, data residency, exclusion from training programs, deletion timelines, or incident response.

Advantages

• External chat and lightweight WebGPU demos can be accessed without registration.
• The WebGPU page lowers the barriers to getting started with local inference, as there is no need to set up a Python environment first.
• It lists R1, R1-Zero, and various distilled versions together, to facilitate an initial understanding of the model family.
• It offers multilingual pages and links for downloading models, making it suitable for learning and navigating through resources.

Restrictions and risks

• The actual model on the home page is DeepSeek-VL2-small, which does not match the title “R1 Online”.
• WebGPU only runs the 1.5B distilled version; its capabilities do not reflect those of the full DeepSeek-R1.
• The entity responsible for operating the site, the available channels for support, and the responsibilities associated with these services are not clear, and it does not represent an official DeepSeek service.
• Private text is an unprocessed template that fails to adequately reflect the chat and external embedded data streams.
• The API prices on this site are outdated and not the actual prices set by the site itself.
• There are no proprietary APIs, SDKs, enterprise solutions, service status information, or official refund policies.
• Model responses may be incorrect, outdated, or fictional, and the reasoning process cannot replace factual evidence.

Frequently Asked Questions

Is this the official website of DeepSeek?

No. The site clearly states that it was created by fans and has no connection to DeepSeek; the official website, applications, and API should be accessed through DeepSeek’s official channels.

Is DeepSeek-R1 used for the chat on the home page?

Not at the moment. The home page actually incorporates an external demonstration of DeepSeek-VL2-small, which is suitable for understanding text and images; however, it cannot be used as an alternative to the R1 inference experience.

What models are run on the WebGPU page?

It runs the browser version of DeepSeek-R1-Distill-Qwen-1.5B. This model is small in size, which makes it convenient to use locally; however, its capabilities and hardware requirements differ significantly from those of the full R1 version.

Is WebGPU inference completely offline?

Inference can be carried out directly in the browser, but the first time it is used, it is necessary to download the web pages, libraries, and model resources. Accessing these pages and downloading these resources may still result in the transmission of network metadata to the website and to third parties.

Can the API prices listed on the page be purchased?

It cannot be considered as a quote from that site. The table refers to historical data from DeepSeek’s official API; the site does not have its own API or settlement system.

Is this site open source?

It is not a verified open-source website. The official DeepSeek-R1 model and its code are licensed under the MIT License, but the source code and licenses of the fan-made versions are not made public.

Can sensitive images be uploaded?

It is not recommended. The image on the home page is used in external demonstrations, and the site’s privacy page does not provide sufficient information regarding who is responsible for processing the data, how it is stored and deleted, and what purposes it is used for in training processes.

How to use DeepSeek-R1 reliably

You can choose the official DeepSeek services, which allow for clear verification of the entity and model version, or download the corresponding weights from the official projects to deploy them on your own. When using distilled models, it is also necessary to determine the underlying model and the relevant licensing terms.

Summary

This site is suitable for use as a resource hub for models and as a platform for demonstrating lightweight WebGPU technologies; however, its name does not correspond to the actual models available on the homepage. Users should consider it to be a third-party fan site, avoid sharing sensitive data, and obtain information regarding R1, APIs, prices, and licenses through official channels.